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Journal articles on the topic 'Real-time correction'

Author: Grafiati

Published: 28 June 2021

Last updated: 21 June 2025

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1

Limpaecher, Alex, Nicolas Feltman, Adrien Treuille, and Michael Cohen. "Real-Time Drawing Assistance through Crowdsourcing." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 1 (November 3, 2013): 101–2. http://dx.doi.org/10.1609/hcomp.v1i1.13058.

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We propose a new method for the large-scale collection and analysis of drawings by using a mobile game specifically designed to collect such data. Analyzing this crowdsourced drawing database, we build a spatially varying model of artistic consensus at the stroke level. We then present a surprisingly simple stroke- correction method which uses our artistic consensus model to improve strokes in real-time. Importantly, our auto-corrections run interactively and appear nearly in- visible to the user while seamlessly preserving artistic intent. Closing the loop, the game itself serves as a plat- form for large-scale evaluation of the effectiveness of our stroke correction algorithm.

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Al-Attas, Syed Haziq Muhammad, Amir Sharifuddin Ab Latip, Ami Hassan Md Din, and Syed Idrus Al-Attas. "Comparison of MyRTKnet Performance with Various Real-Time Corrections Based on Different Time." IOP Conference Series: Earth and Environmental Science 1240, no. 1 (2023): 012005. http://dx.doi.org/10.1088/1755-1315/1240/1/012005.

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Abstract Virtual Reference Station (VRS), Master-Auxiliary Corrections (MAX), Individualised Master-Auxiliary Corrections (IMAX), Nearest Base, and Network D-GNSS are among the Network Real-Time Kinematic (NRTK) techniques supported by the Malaysia Real-Time Kinematic GNSS Network (MyRTKnet) in providing network-based solutions to users. However, different network corrections have different limits due to different characters, thus offering a variety of position accuracy. Therefore, this study evaluated the accuracy of real-time corrections, VRS, MAX, IMAX, D-GNSS, and Nearest Base, for the coordinates at two different times, morning and evening. The study was conducted at two different times to make it easier for users to choose a suitable and quality time to conduct observations. This research was implemented on the pillars at the calibration site of Politeknik Sultan Haji Ahmad Shah (POLISAS) in Kuantan, Pahang. The coordinates in the pillar become a benchmark to differentiate with real-time correction coordinates. The result of that difference can be used to analyse the level of accuracy for real-time corrections. The study’s findings show that the real-time correction accuracy of the VRS type is the most stable and has the highest accuracy. Nearest Base and MAX corrections also give relatively good accuracy and can be improved by increasing observation time and depending on the area. IMAX produces inconsistent results with relatively low accuracy, but some techniques can be applied to obtain good accuracy. D-GNSS type corrections give inconsistent results and low position accuracy as it utilises code measurement only. The research concludes that the best correction is VRS. The Nearest Base and MAX produce acceptable accuracy and can be safely chosen over IMAX and D-GNSS.

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Engelke, Robert M. "Real-time transcription correction system." Journal of the Acoustical Society of America 114, no. 5 (2003): 2544. http://dx.doi.org/10.1121/1.1634110.

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Wu, Ray-Shyan, You-Yu Sin, Jing-Xue Wang, et al. "Real-Time Flood Warning System Application." Water 14, no. 12 (2022): 1866. http://dx.doi.org/10.3390/w14121866.

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The reliability of weather radar data in real-time flood forecasting and early warning system remain ambivalent due to high uncertainty in Quantitative Precipitation Forecasts (QPF). In this study, a methodology is presented with the objective to improve the flood forecasting results with the application of radar rainfall calculated in three different ways. The QPF radar rainfall forecast data of four typhoon events in Fèngshān River Basin, Taiwan, were simulated using the WASH123D numerical model. The simulated results were corrected using a physical real-time correction technique and compared with direct simulation without correction for all three QPF calculation methods. According to model performance evaluation criteria, in the third method of QPF calculation, flood peak error was the lowest in all three methods, indicating better results for flood forecasting and can be used for flood early warning systems. The impact of the real-time correction technique was assessed using mass balance analysis. It was found that flow change is between 16% and 42% from direct simulation, indicating being on the safe side in case of a flood warning. However, the impact of the real-time physical correction on the water level itself is in a reasonable range. Still, QPF rainfall correction/calculation is more important to obtain accurate results for flood forecasting. Therefore, the application of real-time correction to correct the model water level has a certain degree of credibility, which is the mass balance of the model. This approach is recommended for flood forecasting early warning systems.

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Yu, L. H., E. Bozoki, J. Galayda, S. Krinsky, and G. Vignola. "Real time harmonic closed orbit correction." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 284, no. 2-3 (1989): 268–85. http://dx.doi.org/10.1016/0168-9002(89)90292-1.

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Mane, Deepak, Gopal Upadhye, Vinit Gite, Girish Sarwade, Gourav Kamble, and Aditya Pawar. "Smart Yoga Assistant: SVM-based Real-time Pose Detection and Correction System." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7s (2023): 251–62. http://dx.doi.org/10.17762/ijritcc.v11i7s.6997.

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SVM-based Real-time Pose Detection and Correction System refer to a computer system that uses machine learning techniques to detect and correct a person's yoga pose in real-time. This system can act as a virtual yoga assistant, helping people improve their yoga practice by providing immediate feedback on their form and helping to prevent injury. This paper presents a yoga tracker and correction system that uses computer vision and machine learning algorithms to track and correct yoga poses. The system comprises a camera and a computer vision module that captures images of the yoga practitioner and identifies the poses being performed. The machine learning module analyzes the images to provide feedback on the quality of the poses and recommends corrections to improve form and prevent injuries. This paper proposed a customized support vector machine (SVM) based real-time pose detection and correction system that suggests yoga practices based on specific health conditions or diseases. Paper aims to provide a reliable and accessible resource for individuals seeking to use yoga as a complementary approach to managing their health conditions. The system also includes a practitioner’s interface that enables practitioners to receive personalized recommendations for their yoga practice. The system is developed using Python and several open-source libraries, and was tested on a dataset of yoga poses. The hyper parameter gamma tuned to optimize the classification accuracy on our dataset produced 87% which is better than other approaches. The experiment results demonstrate the effectiveness of the system in tracking and correcting yoga poses, and its potential to enhance the quality of yoga practice.

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Karamti, Walid, and Imad Al-Sgir. "Intelligent agents Model with JADE for scheduling analysis and correction of Real-Time Systems." International Journal of Communication Networks and Information Security (IJCNIS) 15, no. 1 (2023): 107–19. http://dx.doi.org/10.17762/ijcnis.v15i1.5762.

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This research proposes a new model for analyzing and correcting non-schedulable partitions in real-time multiprocessor systems, specifically in the context of fault tolerance in distributed networks. The need for such a model arises from current techniques for correcting non-schedulable partitions that must be revised and repartitioning all tasks across processors. The proposed model is based on intelligent agents and implemented using the JADE platform. The model consists of (1) a supervisor agent in the first layer that distributes tasks and manages system correction when a non-schedulable partition is detected; and (2) a second layer composed of partition agents that analyze schedulability, request corrections, and negotiate with the supervisor for additional tasks to correct the entire system. The effectiveness of the proposed model is demonstrated through a case study. Quantitative analysis shows that the proposed model improves fault tolerance in distributed systems and has the potential for further enhancement by adding communicative tasks, heterogeneous processors, and other improvements.

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Xiong, Yuanhui, Kuijun Wu, Guangbao Yu, Zhenwei Chen, Linmei Liu, and Faquan Li. "Real-Time Monitoring of SO2 Emissions Using a UV Camera with Built-in NO2 and Aerosol Corrections." Sensors 22, no. 10 (2022): 3900. http://dx.doi.org/10.3390/s22103900.

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Nitrogen dioxide (NO2) absorption correction of the sulfur dioxide (SO2) camera was demonstrated for the first time. The key to improving the measurement accuracy is to combine a differential optical absorption spectroscopy (DOAS) instrument with the SO2 camera for the real-time NO2 absorption correction and aerosol scattering correction. This method performs NO2 absorption correction by the correlation between the NO2 column density measurement of the DOAS and the NO2 optical depth of the corresponding channel from the SO2 camera at a narrow wavelength window around 310 and 310 nm. The error of correction method is estimated through comparison with only using the second channel of the traditional SO2 camera to correct for aerosol scattering and it can be reduced by 11.3% after NO2 absorption corrections. We validate the correction method through experiments and demonstrate it to be of greatly improved accuracy. The result shows that the ultraviolet (UV) SO2 camera system with NO2 absorption corrections appears to have great application prospects as a technology for visualized real-time monitoring of SO2 emissions.

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Asensio Ramos, A., J. de la Cruz Rodríguez, and A. Pastor Yabar. "Real-time, multiframe, blind deconvolution of solar images." Astronomy & Astrophysics 620 (December 2018): A73. http://dx.doi.org/10.1051/0004-6361/201833648.

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The quality of images of the Sun obtained from the ground are severely limited by the perturbing effect of the Earth’s turbulent atmosphere. The post-facto correction of the images to compensate for the presence of the atmosphere require the combination of high-order adaptive optics techniques, fast measurements to freeze the turbulent atmosphere, and very time-consuming blind deconvolution algorithms. Under mild seeing conditions, blind deconvolution algorithms can produce images of astonishing quality. They can be very competitive with those obtained from space, with the huge advantage of the flexibility of the instrumentation thanks to the direct access to the telescope. In this contribution we make use of deep learning techniques to significantly accelerate the blind deconvolution process and produce corrected images at a peak rate of ∼100 images per second. We present two different architectures that produce excellent image corrections with noise suppression while maintaining the photometric properties of the images. As a consequence, polarimetric signals can be obtained with standard polarimetric modulation without any significant artifact. With the expected improvements in computer hardware and algorithms, we anticipate that on-site real-time correction of solar images will be possible in the near future.

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Li, Jia Ying, Yun Chen Jiang, and Lei Ren. "Real-Time Infrared Image Non-Uniformity Correction Based on FPGA." Advanced Materials Research 971-973 (June 2014): 1696–99. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1696.

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IRFPA is the main direction of infrared imaging technology at present. It has high sensitivity and detection capability, but it also has disadvantages such as bad non-uniformity. Non-uniformity correction is a key technology in the application of IRFPA. As an applicable and real time non-uniformity correction method, the two-point correction algorithmic and single-point correction algorithmic are used widely. Their flow is simple and fixed. They are also suitable to be implemented by FPGA. In this paper, the two-point and single-point method of non-uniformity correction based on FPGA are introduced. And whether the two-point correction or the single-point correction is taken is determined by external control signal. After the completion of the correction coefficients calculation, the coefficients are written into FLASH so that the data will not be lost when the system is powered off.

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Downie, John D. "Real-time holographic image correction using bacteriorhodopsin." Applied Optics 33, no. 20 (1994): 4353. http://dx.doi.org/10.1364/ao.33.004353.

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Schops, Thomas, Martin R. Oswald, Pablo Speciale, Shuoran Yang, and Marc Pollefeys. "Real-Time View Correction for Mobile Devices." IEEE Transactions on Visualization and Computer Graphics 23, no. 11 (2017): 2455–62. http://dx.doi.org/10.1109/tvcg.2017.2734578.

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Rand, J., A. Hoover, S. Fishel, J. Moss, J. Pappas, and E. Muth. "Real-Time Correction of Heart Interbeat Intervals." IEEE Transactions on Biomedical Engineering 54, no. 5 (2007): 946–50. http://dx.doi.org/10.1109/tbme.2007.893491.

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Wang, C.-Y., P. Elliott, S. Sharma, and J. K. Dewhurst. "Real time scissor correction in TD-DFT." Journal of Physics: Condensed Matter 31, no. 21 (2019): 214002. http://dx.doi.org/10.1088/1361-648x/ab048a.

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van der Kouwe, André, and Anders Dale. "Real-time motion correction using octant navigators." NeuroImage 13, no. 6 (2001): 48. http://dx.doi.org/10.1016/s1053-8119(01)91391-6.

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16

Zhang, Kai. "Gctf: Real-time CTF determination and correction." Journal of Structural Biology 193, no. 1 (2016): 1–12. http://dx.doi.org/10.1016/j.jsb.2015.11.003.

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Glagolev, Vladislav, and Alexander Ladonkin. "Real-time perspective correction in video stream." MATEC Web of Conferences 158 (2018): 01010. http://dx.doi.org/10.1051/matecconf/201815801010.

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The paper describes an algorithm used for software perspective correction. The algorithm uses the camera’s orientation angles and transforms the coordinates of pixels on a source image to coordinates on a virtual image form the camera whose focal plane is perpendicular to the gravity vector. This algorithm can be used as a low-cost replacement of a gyrostabilazer in specific applications that restrict using movable parts or heavy and pricey equipment.

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18

Labde, Sakshi. "Real Time Yoga Posture Recognition and Correction." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 4922–27. https://doi.org/10.22214/ijraset.2025.71355.

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The interest in human pose detection and correction technologies has surged, especially following the COVID-19 pandemic, which underscored the importance of maintaining personal health and fitness. While traditional manual techniques have contributed significantly to this field, their limitations in speed and precision have prompted the search for more advanced solutions. Simultaneously, the rising adoption of digital health tools has intensified the demand for applications that assist individuals in performing exercises correctly from home. Yoga, in particular, requires exact posture alignment to maximize its health benefits and minimize injury risks. However, conventional manual assessment methods often entail lengthy evaluation periods and are prone to errors. In response to these challenges, we’ve developed a real-time yoga posture recognition and correction system powered by a deep learning model. Using the MoveNet Thunder architecture, our solution provides users with instant feedback to help fine-tune their posture and alignment. Alongside visual indicators, the app offers real-time voice guidance, making practice sessions safer, smoother, and more effective. This initiative highlights how AI can revolutionize at-home fitness and promote overall well-being.

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Litzenberg, Dale W., James M. Balter, Scott W. Hadley, et al. "Prostate Intrafraction Translation Margins for Real-Time Monitoring and Correction Strategies." Prostate Cancer 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/130579.

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The purpose of this work is to determine appropriate radiation therapy beam margins to account for intrafraction prostate translations for use with real-time electromagnetic position monitoring and correction strategies. Motion was measured continuously in 35 patients over 1157 fractions at 5 institutions. This data was studied using van Herk's formula of (αΣ+γσ') for situations ranging from no electromagnetic guidance to automated real-time corrections. Without electromagnetic guidance, margins of over 10 mm are necessary to ensure 95% dosimetric coverage while automated electromagnetic guidance allows the margins necessary for intrafraction translations to be reduced to submillimeter levels. Factors such as prostate deformation and rotation, which are not included in this analysis, will become the dominant concerns as margins are reduced. Continuous electromagnetic monitoring and automated correction have the potential to reduce prostate margins to 2-3 mm, while ensuring that a higher percentage of patients (99% versus 90%) receive a greater percentage (99% versus 95%) of the prescription dose.

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Xu, Zhenhao, Rui Shang, Chengfa Gao, et al. "Temporal Characteristics Based Outlier Detection and Prediction Methods for PPP-B2b Orbit and Clock Corrections." Remote Sensing 16, no. 13 (2024): 2337. http://dx.doi.org/10.3390/rs16132337.

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The BeiDou Global Navigation Satellite System (BDS-3) provides real-time precise point positioning (PPP) service via B2b signals, offering real-time decimeter-level positioning for users in China and surrounding areas. However, common interruptions and outliers in PPP-B2b services arise due to factors such as the Geostationary Orbit (GEO) satellite “south wall effect”, Issue of Data (IOD) matching errors, and PPP-B2b signal broadcast priorities, posing challenges to continuous high-precision positioning. This study meticulously examines the completeness, continuity, and jumps in PPP-B2b orbit and clock correction using extensive observational data. Based on this analysis, a two-step method for detecting outliers in PPP-B2b orbit and clock corrections is devised, leveraging epoch differences and median absolute deviation. Subsequently, distinct prediction methods are developed for BDS-3 and GPS orbit and clock corrections. Results from simulated and real-time dynamic positioning experiments indicate that predicted corrections can maintain the same accuracy as normal correction values for up to 10 min and sustain decimeter-level positioning accuracy within 30 min. The adoption of predicted correction values significantly enhances the duration of sustaining real-time PPP during signal interruptions.

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Ding, Jin, Jinbing Gao, Guoping Zhang, et al. "A Rolling Real-Time Correction Method for Minute Precipitation Forecast Based on Weather Radars." Water 15, no. 10 (2023): 1872. http://dx.doi.org/10.3390/w15101872.

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The quantitative precipitation estimation by weather radar plays an important role in observations and forecasts of meteorological processes. The National Minute Quantitative Precipitation Forecast system of China (MQPF), providing location-based refined short-term and imminent precipitation forecasting services, filled the gap in the official minute precipitation service products in China’s meteorological field. However, due to the technical limitations of radar itself and the complexity of the atmosphere, the corresponding relationship between radar echoes and surface precipitation is unstable. Based on radar and precipitation data from meteorological stations, a rolling real-time correction method is proposed to improve precipitation prediction accuracy through rolling correction of spatial and temporal structural errors in MQPF products. The results show the following: (1) Although this method may lead to a certain increase in the missing ratio, the significant improvement in the false alarm ratio after rolling correction has a positive guiding effect on short-term public meteorological services. (2) Regarding the time to complete rolling correction, the longest and shortest times appear in April and December, respectively. The mean running time to achieve correction of spatial and temporal error corrections ranges from 3.8 s to 6.4 s and 7.7 s to 11.5 s, respectively, which fully meets the real-time operational requirements of radar business.

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Chumchean, Siriluk, Ashish Sharma, and Alan Seed. "An Integrated Approach to Error Correction for Real-Time Radar-Rainfall Estimation." Journal of Atmospheric and Oceanic Technology 23, no. 1 (2006): 67–79. http://dx.doi.org/10.1175/jtech1832.1.

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Abstract A procedure for estimating radar rainfall in real time consists of three main steps: 1) the measurement of reflectivity and removal of known sources of errors, 2) the conversion of the reflectivity to a rainfall rate (Z–R conversion), and 3) the adjustment of the mean field bias as assessed using a rain gauge network. Error correction is associated with the first two steps and incorporates removing erroneous measurements and correcting biases in the Z–R conversion. This paper investigates the relative importance of error correction and the mean field bias–adjustment processes. In addition to the correction for ground clutter, the bright band, and hail, the two error correction strategies considered here are 1) a scale transformation function to remove range-dependent bias in measured reflectivity resulting from an increase in observation volume with range, and 2) the classification of storm types to account for the variation in Z–R relationships for convective and stratiform rainfall. The mean field bias is removed using two alternatives: 1) estimation of the bias at each time step based on the sample of observations available, and 2) use of a Kalman filter to estimate the bias under assumptions of a Markovian dependence structure. A 7-month record of radar and rain gauge rainfall for Sydney, Australia, were used in this study. The results show a stepwise decrease in the root-mean-square error (rmse) of radar rainfall with added levels of error correction using either of the two mean field bias–adjustment methods considered in our study. It was found that although the effects of the two error correction strategies were small compared to bias adjustment, they do form an important step of radar-rainfall estimation.

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Mircea Ionut, Olteanu, Badau Dana, and Martoma Alina. "Study on the Identification of Execution Errors, Causes, and Specific Corrective Kinetic and Prophylactic Means in Free Throws in Basketball." GYMNASIUM 25, no. 1 (2024): 94–109. http://dx.doi.org/10.29081/gsjesh.2024.25.1.07.

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The identification of execution errors in real-time correction through an innovative specific device to free throw refinement, and through corrective kinetic and prophylactic exercises adapted to basketball game. The study included 92 subjects structured into sports categories: U14, U16, U18, and by gender: female (46 subjects) and male (46 subjects). Subjects were observed to identify the incidence of execution errors in free throws, their causes and correction methods during the study's testing. The study results highlight the decrease in the number of execution errors between the final and initial testing due to the implementation of innovative technology specific to free throw refinement and the application of specific corrective kinetic and prophylactic exercises. For all junior and gender categories of the study, the number of errors decreased in the final testing compared to the initial one, highlighting the importance of identifying errors and causes in real-time and correcting them through specific means.

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Kim, Jeongrae, and Mingyu Kim. "ARMA Prediction of SBAS Ephemeris and Clock Corrections for Low Earth Orbiting Satellites." International Journal of Aerospace Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/165178.

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For low earth orbit (LEO) satellite GPS receivers, space-based augmentation system (SBAS) ephemeris/clock corrections can be applied to improve positioning accuracy in real time. The SBAS correction is only available within its service area, and the prediction of the SBAS corrections during the outage period can extend the coverage area. Two time series forecasting models, autoregressive moving average (ARMA) and autoregressive (AR), are proposed to predict the corrections outside the service area. A simulated GPS satellite visibility condition is applied to the WAAS correction data, and the prediction accuracy degradation, along with the time, is investigated. Prediction results using the SBAS rate of change information are compared, and the ARMA method yields a better accuracy than the rate method. The error reductions of the ephemeris and clock by the ARMA method over the rate method are 37.8% and 38.5%, respectively. The AR method shows a slightly better orbit accuracy than the rate method, but its clock accuracy is even worse than the rate method. If the SBAS correction is sufficiently accurate comparing with the required ephemeris accuracy of a real-time navigation filter, then the predicted SBAS correction may improve orbit determination accuracy.

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Kelevitz, Krisztina, Kristy F. Tiampo, and Brianna D. Corsa. "Improved Real-Time Natural Hazard Monitoring Using Automated DInSAR Time Series." Remote Sensing 13, no. 5 (2021): 867. http://dx.doi.org/10.3390/rs13050867.

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As part of the collaborative GeoSciFramework project, we are establising a monitoring system for the Yellowstone volcanic area that integrates multiple geodetic and seismic data sets into an advanced cyber-infrastructure framework that will enable real-time streaming data analytics and machine learning and allow us to better characterize associated long- and short-term hazards. The goal is to continuously ingest both remote sensing (GNSS, DInSAR) and ground-based (seismic, thermal and gas observations, strainmeter, tiltmeter and gravity measurements) data and query and analyse them in near-real time. In this study, we focus on DInSAR data processing and the effects from using various atmospheric corrections and real-time orbits on the automated processing and results. We find that the atmospheric correction provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) is currently the most optimal for automated DInSAR processing and that the use of real-time orbits is sufficient for the early-warning application in question. We show analysis of atmospheric corrections and using real-time orbits in a test case over the Kilauea volcanic area in Hawaii. Finally, using these findings, we present results of displacement time series in the Yellowstone area between May 2018 and October 2019, which are in good agreement with GNSS data where available. These results will contribute to a baseline model that will be the basis of a future early-warning system that will be continuously updated with new DInSAR data acquisitions.

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Guo, Jiang, Jun Cheng, Yu Guo, and Jian Xin Pang. "A Real-Time Dynamic Gesture Recognition System." Applied Mechanics and Materials 333-335 (July 2013): 849–55. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.849.

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In this paper, we present a dynamic gesture recognition system. We focus on the visual sensory information to recognize human activity in form of hand movements from a small, predefined vocabulary. A fast and effective method is presented for hand detection and tracking at first for the trajectory extraction. A novel trajectory correction method is applied for simply but effectively trajectory correction. Gesture recognition is achieved by means of a matching technique by determining the distance between the unknown input direction code sequence and a set of previously defined templates. A dynamic time warping (DTW) algorithm is used to perform the time alignment and normalization by computing a temporal transformation allowing the two signals to be matched. Experiment results show our proposed gesture recognition system achieve well result in real time.

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YANG, Ci-Yin, Jian-Ping ZHANG, and Li-Hua CAO. "Infrared radiation measurement based on real-time correction." JOURNAL OF INFRARED AND MILLIMETER WAVES 30, no. 3 (2012): 284–88. http://dx.doi.org/10.3724/sp.j.1010.2011.00284.

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Li, Gansheng. "Correction to Making C++ Concurrent and Real-time." ACM SIGPLAN Notices 33, no. 4 (1998): 27. http://dx.doi.org/10.1145/278283.607953.

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Kandel, Mikhail E., Michael Fanous, Catherine Best-Popescu, and Gabriel Popescu. "Real-time halo correction in phase contrast imaging." Biomedical Optics Express 9, no. 2 (2018): 623. http://dx.doi.org/10.1364/boe.9.000623.

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Rukosuev, A. L., A. V. Kudryashov, A. N. Lylova, V. V. Samarkin, and Yu V. Sheldakova. "Adaptive optics system for real-time wavefront correction." Atmospheric and Oceanic Optics 28, no. 4 (2015): 381–86. http://dx.doi.org/10.1134/s1024856015040119.

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Bue, Brian D., David R. Thompson, Michael Eastwood, et al. "Real-Time Atmospheric Correction of AVIRIS-NG Imagery." IEEE Transactions on Geoscience and Remote Sensing 53, no. 12 (2015): 6419–28. http://dx.doi.org/10.1109/tgrs.2015.2439215.

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Lee, Christine C., Clifford R. Jack, Roger C. Grimm, et al. "Real-time adaptive motion correction in functional MRI." Magnetic Resonance in Medicine 36, no. 3 (1996): 436–44. http://dx.doi.org/10.1002/mrm.1910360316.

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Benner, Thomas, André J. W. van der Kouwe, John E. Kirsch, and A. Gregory Sorensen. "Real-time RF pulse adjustment forB0 drift correction." Magnetic Resonance in Medicine 56, no. 1 (2006): 204–9. http://dx.doi.org/10.1002/mrm.20936.

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Di Giuseppe, Francesca, Franco Molteni, and Emanuel Dutra. "Real-time correction of ERA-Interim monthly rainfall." Geophysical Research Letters 40, no. 14 (2013): 3750–55. http://dx.doi.org/10.1002/grl.50670.

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Li, Bing, Zheng Yu Yang, and Bao Ma. "Research of IRFPA Non-uniformity Real-Time Correction Based on SOPC." Key Engineering Materials 474-476 (April 2011): 277–82. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.277.

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<b>N</b>on-uniformity of infrared focal plane arrays (IRFPA) decreases the quality of the infrared imaging system greatly, so it is necessary to correct non-uniformity. Now the scene-based correction is being the focus of the study at home and abroad. Firstly, researching on normalized BP artificial neural network correction method in this paper, and then building a SOPC system on Altera's Stratix II EP2S60 DSP Development Board to realize the normalized BP real-time correction non-uniformity. The simulation results show that the SOPC system would meet the requirements of real-time correction. At the same time, the other method could be better to upgrade.

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Roj, J. "Neural Network Based Real-time Correction of Transducer Dynamic Errors." Measurement Science Review 13, no. 6 (2013): 286–91. http://dx.doi.org/10.2478/msr-2013-0042.

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Abstract In order to carry out real-time dynamic error correction of transducers described by a linear differential equation, a novel recurrent neural network was developed. The network structure is based on solving this equation with respect to the input quantity when using the state variables. It is shown that such a real-time correction can be carried out using simple linear perceptrons. Due to the use of a neural technique, knowledge of the dynamic parameters of the transducer is not necessary. Theoretical considerations are illustrated by the results of simulation studies performed for the modeled second order transducer. The most important properties of the neural dynamic error correction, when emphasizing the fundamental advantages and disadvantages, are discussed.

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Lu, Hua-pu, Zhi-yuan Sun, Wen-cong Qu, and Ling Wang. "Real-Time Corrected Traffic Correlation Model for Traffic Flow Forecasting." Mathematical Problems in Engineering 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/348036.

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This paper focuses on the problems of short-term traffic flow forecasting. The main goal is to put forward traffic correlation model and real-time correction algorithm for traffic flow forecasting. Traffic correlation model is established based on the temporal-spatial-historical correlation characteristic of traffic big data. In order to simplify the traffic correlation model, this paper presents correction coefficients optimization algorithm. Considering multistate characteristic of traffic big data, a dynamic part is added to traffic correlation model. Real-time correction algorithm based on Fuzzy Neural Network is presented to overcome the nonlinear mapping problems. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling methods.

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Suryawanshi, Prof Vaishali, Pranav Hare, Archi Goyal, and Om Ahire. "Gym Tracker System Using AI-Driven Pose Estimation and Real-Time Exercise Correction." International Journal of Research and Scientific Innovation XII, no. IV (2025): 1374–81. https://doi.org/10.51244/ijrsi.2025.12040113.

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This paper explores the development of a gym tracker system utilising AI-driven pose estimation and real-time exercise correction, leveraging OpenCV and MediaPipe. The system is designed to monitor user movements during workouts, identifying common posture errors and proIIding immediate feedback to enhance form and prevent injury. By employing computer vision techniques for keypoint detection and tracking, the system analyses exercise poses, compares them to ideal models, and offers corrective guidance. This approach aims to improve workout efficiency and safety, making AI-powered fitness tracking accessible and effective for users of all skill levels.

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Xie, Kun, Wenguang Liu, Qiong Zhou, Zongfu Jiang, Fengjie Xi, and Xiaojun Xu. "Real-time phase measurement and correction of dynamic multimode beam using a single spatial light modulator." Chinese Optics Letters 18, no. 1 (2020): 011404. http://dx.doi.org/10.3788/col202018.011404.

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Li, Hai, Xiaoyang Wang, Shihui Wu, and Songze Ye. "Improving Real-Time Gear Contact Fatigue Inspection with Machine Vision." International Journal of Computer Science and Information Technology 4, no. 3 (2024): 103–14. https://doi.org/10.62051/ijcsit.v4n3.11.

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A fast gear image correction algorithm is proposed for the real-time detection of gear pitting failure area in gear contact fatigue test. Based on the fact that gear pitting first appears near the pitch circle of the gear and expands to the root circle [1], the algorithm uses the pitch circle as the basis for the camera scanning line frequency calculation, and uses the pitch circle as the segmentation point to calculate the actual pixel value of the gear meshing surface, which leads to a reduction in the amount of computational parameters. The trigonometric function calculation method instead of the involute parametric equation curve product formula is used, which makes the calculation speed increase. Based on the principle of involute gear meshing and the principle of scanning camera shooting, the pixel value of gear meshing surface imaging is deduced, as well as the formula for calculating the pitting rate of gears based on the pixel value is proposed. The experimental results show that the average absolute error of the gear image fast correction algorithm proposed in this paper is 2.2868%, and the average relative error is 0.11059mm2, the algorithm is relative to the gear mesh surface correction algorithm [2] in the detection of the gear pitting area of the absolute error decreases by 0.1412%, and the relative error decreases by 0.0127mm2, and the computational complexity for the gear mesh surface correction algorithm 1/5 of that of the gear mesh surface correction algorithm, and finally combined with the pixel value-based gear pitting rate calculation formula, thus accurately detecting the time of gear pitting failure.

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Yu, Xiao Yu, and Yan Liu. "FBG Demodulation System Based on Real-Time Correction Technology." Advanced Materials Research 505 (April 2012): 362–66. http://dx.doi.org/10.4028/www.scientific.net/amr.505.362.

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The system error of the FBG demodulation system based on tunable fiber Fabry-Perot (F-P) interferometer increases due to the uncertain relationship of driving voltage and the scanning wave peak. So the real-time correction technology is studied here. A parallel real-time correction system is designed to correct nonlinear problems of PZT and structural errors of the tunable FP interferometer. The relation between PZT driving voltage and the peak of tunable FP interferometer is analyzed by the experiments. Then a fast segmentation algorithm is designed. Then a signal processing system is designed using FPGA, which guarantees real-time work of the system by integrating the demodulation system control, filter calculation and data compression circuits into one FPGA chip. Experimental results show that the system described here solves the accuracy problem caused by the tunable FP interferometer.

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Li, Qian, Caisong Li, Huanfei Yu, Jinglin Qian, Linlin Hu, and Hangjian Ge. "System response curve correction method of runoff error for real-time flood forecast." Hydrology Research 51, no. 6 (2020): 1312–31. http://dx.doi.org/10.2166/nh.2020.048.

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Abstract Multiple factors including rainfall and underlying surface conditions make river basin real-time flood forecasting very challenging. It is often necessary to use real-time correction techniques to modify the forecasting results so that they reach satisfactory accuracy. There are many such techniques in use today; however, they tend to have weak physical conceptual basis, relatively short forecast periods, unsatisfactory correction effects, and other problems. The mechanism that affects real-time flood forecasting error is very complicated. The strongest influencing factors corresponding to this mechanism affect the runoff yield of the forecast model. This paper proposes a feedback correction algorithm that traces back to the source of information, namely, modifies the watershed runoff. The runoff yield error is investigated using the principle of least squares estimation. A unit hydrograph is introduced into the real-time flood forecast correction; a feedback correction model that traces back to the source of information. The model is established and verified by comparison with an ideal model. The correction effects of the runoff yield errors are also compared in different ranges. The proposed method shows stronger correction effect and enhanced prediction accuracy than the traditional method. It is also simple in structure and has a clear physical concept without requiring added parameters or forecast period truncation. It is readily applicable in actual river basin flood forecasting scenarios.

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D. Mahesh Kumar, Aravinda H. S., Thejaswini P. ,. Anu H. ,. "AN ADAPTIVE ALGORITHM BASED AUTHENTICATION SYSTEM FOR REAL-TIME BIOMETRIC TIME-ATTENDANCE SYSTEM." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (2021): 77–90. http://dx.doi.org/10.17762/itii.v9i1.104.

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Biometric features are physical and biological characteristics that are unique to a person and can be used to accomplish authentication based on the particular modality. The main purpose of implementation of an Adaptive auto-correction technique for biometric time-attendance system is to improve the matching rate of fingerprint verification under the condition when fingerprint patterns vary due to environmental parameter like temperature. An Adaptive auto-correction technique is proposed which auto-corrects the reference fingerprint template at the time of genuine user rejection. The proposed technique is implemented on commercially available biometric device which uses Innovatrics, a standard commercially available extractor and matcher. Evaluation is carried out on 250 fingerprint templates of 10-users captured at varying temperature from 250C to 00C. The experimental analysis will be carried out to improve the recognition rate.

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Xie, Quancai, Qiang Ma, Jingfa Zhang, and Haiying Yu. "Study on real-time correction of site amplification factor." Natural Hazards and Earth System Sciences 19, no. 12 (2019): 2827–39. http://dx.doi.org/10.5194/nhess-19-2827-2019.

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Abstract. The site amplification factor was usually considered to be scalar values, such as amplification of peak ground acceleration or peak ground velocity, or increments of seismic intensity in the earthquake early warning (EEW) system or seismic-intensity repaid report system. This paper focuses on evaluating an infinite impulse recursive filter method that could produce frequency-dependent site amplification and compare the performance of the scalar-value method with the infinite impulse recursive filter method. A large number of strong motion data of IBRH10 and IBRH19 of the Kiban Kyoshin network (KiK-net) triggered in more than 1000 earthquakes from 2004 to 2012 were selected carefully and used to obtain the relative site amplification ratio; we model the relative site amplification factor with a casual filter. Then we make a simulation from the borehole to the surface and also simulate from the front-detection station to the far-field station. Compared to different simulation cases, it can easily be found that this method could produce different amplification factors for different earthquakes and could reflect the frequency-dependent nature of site amplification. Through these simulations between two stations, we can find that the frequency-dependent correction for site amplification shows better performance than the amplification factor relative to velocity (ARV) method and station correction method. It also shows better performance than the average level and the highest level of the Japan Meteorological Agency (JMA) earthquake early warning system in ground motion prediction. Some cases in which simulation did not work very well were also found; possible reasons and problems were analyzed and addressed. This method pays attention to the amplitude and ignores the phase characteristics; this problem may be improved by the seismic-interferometry method. Frequency-dependent correction for site amplification in the time domain highly improves the accuracy of predicting ground motion in real time.

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Zhang, Dongying, Ting Du, Hao Yin, Shiwei Xia, and Huiting Zhang. "Multi-Time-Scale Coordinated Operation of a Combined System with Wind-Solar-Thermal-Hydro Power and Battery Units." Applied Sciences 9, no. 17 (2019): 3574. http://dx.doi.org/10.3390/app9173574.

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The grid connection of intermittent energy sources such as wind power and photovoltaic power generation brings new challenges for the economic and safe operation of renewable power systems. To address these challenges, a multi-time-scale active power coordinated operation method, consisting of day-ahead scheduling, hour-level rolling corrective scheduling, and real-time corrective scheduling, is proposed for the combined operation of wind-photovoltaic-thermal-hydro power and battery (WPTHB) to handle renewable power fluctuations. In day-ahead scheduling, the optimal power outputs of thermal power units, hydro-pumped storage units, and batteries are solved with the purpose of minimizing the total power generation cost. In hour-level rolling corrective scheduling, the power output plan of thermal power units and pumped storage units is modified to minimize the correction cost based on the on-off state of thermal power units determined in day-ahead scheduling. In real-time corrective scheduling stage, the feedback correction and rolling optimization-based model predictive control algorithm is adopted to modify the power output of thermal power units, hydro-pumped storage units, and batteries optimized in hour-level rolling correction scheduling, so as to ensure the economy of the correction plan and the static security of system operation. Finally, simulation results demonstrated that the proposed method can accurately track system power fluctuations, and ensure the economic and security operation of a multi-energy-generation system.

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LI Geng-fei, 李赓飞, 李桂菊 LI Gui-ju, 韩广良 HAN Guang-liang, 刘培勋 LIU Pei-xun, and 江山 JIANG Shan. "Real-time non-uniformity correction of infrared imaging system." Optics and Precision Engineering 24, no. 11 (2016): 2841–47. http://dx.doi.org/10.3788/ope.20162411.2841.

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Guo, Yudong, Juyong Zhang, Yihua Chen, Hongrui Cai, Zhangjin Huang, and Bailin Deng. "Real-time face view correction for front-facing cameras." Computational Visual Media 7, no. 4 (2021): 437–52. http://dx.doi.org/10.1007/s41095-021-0215-y.

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AbstractFace views are particularly important in person-to-person communication. Differenes between the camera location and the face orientation can result in undesirable facial appearances of the participants during video conferencing. This phenomenon is particularly noticeable when using devices where the front-facing camera is placed in unconventional locations such as below the display or within the keyboard. In this paper, we take a video stream from a single RGB camera as input, and generate a video stream that emulates the view from a virtual camera at a designated location. The most challenging issue in this problem is that the corrected view often needs out-of-plane head rotations. To address this challenge, we reconstruct the 3D face shape and re-render it into synthesized frames according to the virtual camera location. To output the corrected video stream with natural appearance in real time, we propose several novel techniques including accurate eyebrow reconstruction, high-quality blending between the corrected face image and background, and template-based 3D reconstruction of glasses. Our system works well for different lighting conditions and skin tones, and can handle users wearing glasses. Extensive experiments and user studies demonstrate that our method provides high-quality results.

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Jereb, Zmago, and Janez Diaci. "Real-time geometrical correction of video image using FPGA." IEICE Electronics Express 7, no. 5 (2010): 346–51. http://dx.doi.org/10.1587/elex.7.346.

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Kwon, Yejin, and Dongho Kim. "Real-Time Workout Posture Correction using OpenCV and MediaPipe." Journal of Korean Institute of Information Technology 20, no. 1 (2022): 199–208. http://dx.doi.org/10.14801/jkiit.2022.20.1.199.

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Mazurek, P. "Real–Time Correction of Cameras’ Geometric Distortions using GPGPU." IFAC Proceedings Volumes 42, no. 13 (2009): 332–35. http://dx.doi.org/10.3182/20090819-3-pl-3002.00058.

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