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Articoli di riviste sul tema "Artificial Intelligence and Signal and Image Processing"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 20 febbraio 2023

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1

Kim, Byung-Gyu, and Dong-San Jun. "Artificial Intelligence for Multimedia Signal Processing." Applied Sciences 12, no. 15 (July 22, 2022): 7358. http://dx.doi.org/10.3390/app12157358.

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2

Zhang, Xin, and Wang Dahu. "Application of artificial intelligence algorithms in image processing." Journal of Visual Communication and Image Representation 61 (May 2019): 42–49. http://dx.doi.org/10.1016/j.jvcir.2019.03.004.

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3

Wei, Hui, Luping Wang, Shanshan Wang, Yuxiang Jiang, and Jingmeng Li. "A Signal-Processing Neural Model Based on Biological Retina." Electronics 9, no. 1 (December 27, 2019): 35. http://dx.doi.org/10.3390/electronics9010035.

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Image signal processing has considerable value in artificial intelligence. However, due to the diverse disturbance (e.g., color, noise), the image signal processing, especially the representation of the signal, remains a big challenge. In the human visual system, it has been justified that simple cells in the primary visual cortex are obviously sensitive to vision signals with partial orientation features. In other words, the image signals are extracted and described along the pathway of visual processing. Inspired by this neural mechanism of the primary visual cortex, it is possible to build

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4

Raghavendra, U., U. Rajendra Acharya, and Hojjat Adeli. "Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders." European Neurology 82, no. 1-3 (2019): 41–64. http://dx.doi.org/10.1159/000504292.

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Background: Authors have been advocating the research ideology that a computer-aided diagnosis (CAD) system trained using lots of patient data and physiological signals and images based on adroit integration of advanced signal processing and artificial intelligence (AI)/machine learning techniques in an automated fashion can assist neurologists, neurosurgeons, radiologists, and other medical providers to make better clinical decisions. Summary: This paper presents a state-of-the-art review of research on automated diagnosis of 5 neurological disorders in the past 2 decades using AI techniques:

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5

Yu, Frances, and Haibin Duan. "Meta-heuristic intelligence based image processing." Pattern Recognition Letters 31, no. 13 (October 2010): 1749. http://dx.doi.org/10.1016/j.patrec.2010.06.006.

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6

Mohammad-Djafari, Ali. "Interaction between Model Based Signal and Image Processing, Machine Learning and Artificial Intelligence." Proceedings 33, no. 1 (November 28, 2019): 16. http://dx.doi.org/10.3390/proceedings2019033016.

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Signale and image processing has always been the main tools in many area and in particular in Medical and Biomedical applications. Nowadays, there are great number of toolboxes, general purpose and very specialized, in which classical techniques are implemented and can be used: all the transformation based methods (Fourier, Wavelets, ...) as well as model based and iterative regularization methods. Statistical methods have also shown their success in some area when parametric models are available. Bayesian inference based methods had great success, in particular, when the data are noisy, uncer

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Shi, Zengfang, and Meizhou Liu. "Moving Vehicle Detection and Recognition Technology based on Artificial Intelligence." International Journal of Circuits, Systems and Signal Processing 16 (January 13, 2022): 399–405. http://dx.doi.org/10.46300/9106.2022.16.49.

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The existing target detection and recognition technology has the problem of fuzzy features of moving vehicles, which leads to poor detection effect. A moving car detection and recognition technology based on artificial intelligence is designed. The point operation is adopted to enhance the high frequency information of the image, increase the image contrast, and delineate the video image tracking target. The motion vector similarity is used to predict the moving target area in the next frame of the image. The texture features of the moving car are extracted by artificial intelligence, and the

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8

Zhao, Qian, and Hong Zhang. "Automatic Color Extraction Algorithm of Graphic Design Image Based on Artificial Intelligence." International Journal of Circuits, Systems and Signal Processing 16 (January 12, 2022): 374–84. http://dx.doi.org/10.46300/9106.2022.16.46.

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The extraction of color features plays an important role in image recognition and image retrieval. In the past, feature extraction mainly depends on manual or supervised learning, which limits the automation of the whole recognition or retrieval process. In order to solve the above problems, an automatic color extraction algorithm based on artificial intelligence is proposed. According to the characteristics of BMP image, the paper makes use of the conversion between image color space and realizes it in the visual C++6.0 environment. The experimental results show that the algorithm realizes th

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9

Zhao, Ying, and Guocheng Wei. "Using an Improved PSO-SVM Model to Recognize and Classify the Image Signals." Complexity 2021 (June 16, 2021): 1–12. http://dx.doi.org/10.1155/2021/8328532.

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Image recognition is an important field of artificial intelligence. Its basic idea is to use computers to automatically classify different scenes in the acquired images, instead of traditional manual classification tasks. In this paper, through the analysis of rough set theory and artificial intelligence network, as well as the role of the two in image recognition, the rough set theory and artificial intelligence network are organically combined, and a network based on rough set theory and artificial intelligence network is proposed. Using BP artificial intelligence network model, improved BP

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10

Mon, Yi-Jen. "Vision Robot Path Control Based on Artificial Intelligence Image Classification and Sustainable Ultrasonic Signal Transformation Technology." Sustainability 14, no. 9 (April 28, 2022): 5335. http://dx.doi.org/10.3390/su14095335.

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The unsupervised algorithm of artificial intelligence (AI), named ART (Adaptive Resonance Theory), is used to first roughly classify an image, that is, after the image is processed by the edge filtering technology, the image window is divided into 25 square areas of 5 rows and 5 columns, and then, according to the location of the edge of the image, it determines whether the robot should go straight (represented by S), turn around (represented by A), stop (T), turn left (represented by L), or turn right (represented by R). Then, after sustainable ultrasonic signal acquisition and transformation

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11

Hung, Kuo-Ching, Meng-Chun Lin, and Sheng-Fuu Lin. "A Novel Power-Saving Reversing Camera System with Artificial Intelligence Object Detection." Electronics 11, no. 2 (January 17, 2022): 282. http://dx.doi.org/10.3390/electronics11020282.

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According to a study by the Insurance Institute for Highway Safety (IIHS), the driving collision rate of using only the reversing camera system is lower than that of using both the reversing camera system and the reversing radar. In this article, we implemented a reversing camera system with artificial intelligence object detection to increase the information of the reversing image. Our system consists of an image processing chip (IPC) with wide-angle image distortion correction and an image buffer controller, a low-power KL520 chip and an optimized artificial intelligence model MobileNetV2-YO

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12

Love, P. L., and M. Simaan. "Segmentation of a seismic section using image processing and artificial intelligence techniques." Pattern Recognition 18, no. 6 (January 1985): 409–19. http://dx.doi.org/10.1016/0031-3203(85)90011-1.

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Rajan, K., KS Sangunni, and J. Ramakrishna. "Dual-DSP system for signal and image processing." Microprocessors and Microsystems 17, no. 9 (November 1993): 556–60. http://dx.doi.org/10.1016/s0141-9331(09)91007-9.

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14

Yang, Yue, Wei Liu, Zuoxun Zeng, and Wei Xue. "Signal Processing on Precursory “Fingerprint” Image Pattern Feature of Yushu Earthquake." Journal of Advanced Computational Intelligence and Intelligent Informatics 20, no. 7 (December 20, 2016): 1165–69. http://dx.doi.org/10.20965/jaciii.2016.p1165.

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Precursory earthquake data are linked closely to the earthquake processes. Taking the Tibetan Autonomous Region’s Yushu County earthquake as an example, we analyzed three types of earthquake signals and studied a modeling method for self-adaptative matching warning data on precursory data’s fingerprint features. We calculated different timescale features of precursory fingerprint pattern images based on statistical physics and image matching. We also developed corresponding fuzzy discriminant rules and established a database of warning-image fingerprint pattern features for the Yushu County re

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15

Zheng, Xianwei, Yuan Yan Tang, Jiantao Zhou, Jianjia Pan, Shouzhi Yang, Youfa Li, and Patrick S. P. Wang. "Multi-Level Downsampling of Graph Signals via Improved Maximum Spanning Trees." International Journal of Pattern Recognition and Artificial Intelligence 33, no. 03 (February 19, 2019): 1958005. http://dx.doi.org/10.1142/s0218001419580059.

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Graph signal processing (GSP) is an emerging field in the signal processing community. Novel GSP-based transforms, such as graph Fourier transform and graph wavelet filter banks, have been successfully utilized in image processing and pattern recognition. As a rapidly developing research area, graph signal processing aims to extend classical signal processing techniques to signals with irregular underlying structures. One of the hot topics in GSP is to develop multi-scale transforms such that novel GSP-based techniques can be applied in image processing or other related areas. For designing gr

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Sahith, Jai Krishna. "RECOGNITION OF AIRCRAFT IN REMOTE SENSING IMAGES USING CONVOLUTIONAL NEURAL NETWORK." Journal of Airline Operations and Aviation Management 1, no. 1 (July 25, 2022): 63–70. http://dx.doi.org/10.56801/jaoam.v1i1.8.

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   Picture processing is a stand-alone, non-human image comprehension system that is one of the major breakthroughs (IUS). When one tries to explain what comprehension is, the effort of comprehending images becomes massive. In addition to classical signal processing, pattern recognition and artificial intelligence are applied. The early phases of the picture comprehension process might be called scene analysis methods that use edge and texture segmentation. As a result, putting a man in a signal processing loop at particular sensors, such as remotely piloted vehicles, satelli

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Allende, Héctor, Jorge Galbiati, and Ronny Vallejos. "Robust image modeling on image processing." Pattern Recognition Letters 22, no. 11 (September 2001): 1219–31. http://dx.doi.org/10.1016/s0167-8655(01)00054-x.

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18

Owoeye, Oluwatobi M., and Olusola Abayomi Ojo-Omoniyi. "Deep Learning and Computer Vision: Machine Learning Analysis and Image Processing of Puromycin Treated Microscopy." International Journal of Current Microbiology and Applied Sciences 11, no. 6 (June 10, 2022): 119–33. http://dx.doi.org/10.20546/ijcmas.2022.1106.014.

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Digital image processing involves the usage of a functional algorithm to process images with special regions of interest. In most case scenarios, this is termed as an active aspect of digital signal processing; image processing comes with several rewards over analog image processing. Its relevance and application spans Autonomous Vehicles, Biometric fingerprint technologies as well as Face recognition applications. Reliable statistics through feature engineering from the image can be extracted and in turn serve as focus points of deep learning insights. Besides, its application in monitoring C

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19

Mishra, Ishani, and Sanjay Jain. "Soft computing based compressive sensing techniques in signal processing: A comprehensive review." Journal of Intelligent Systems 30, no. 1 (September 11, 2020): 312–26. http://dx.doi.org/10.1515/jisys-2019-0215.

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Abstract In this modern world, a massive amount of data is processed and broadcasted daily. This includes the use of high energy, massive use of memory space, and increased power use. In a few applications, for example, image processing, signal processing, and possession of data signals, etc., the signals included can be viewed as light in a few spaces. The compressive sensing theory could be an appropriate contender to manage these limitations. “Compressive Sensing theory” preserves extremely helpful while signals are sparse or compressible. It very well may be utilized to recoup light or com

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20

Alcalde, Cristina, Ana Burusco, and Ramón Fuentes-González. "Application of the L-fuzzy concept analysis in the morphological image and signal processing." Annals of Mathematics and Artificial Intelligence 72, no. 1-2 (January 18, 2014): 115–28. http://dx.doi.org/10.1007/s10472-014-9397-7.

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Abbod, Maysam, and Jiann-Shing Shieh. "Special Issue “Advanced Signal Processing in Intelligent Systems for Health Monitoring”." Sensors 19, no. 21 (October 31, 2019): 4727. http://dx.doi.org/10.3390/s19214727.

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Recently, significant developments have been achieved in the field of artificial intelligence, in particular the introduction of deep learning technology that has improved the learning and prediction accuracy to unpresented levels, especially when dealing with big data and high-resolution images. Significant developments have occurred in the area of medical signal processing, measurement techniques, and health monitoring, such as vital biological signs for biomedical systems and noise and vibration of mechanical systems, which are carried out by instruments that generate large data sets. These

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22

Xue, Bin, and Zhisheng Wu. "Key Technologies of Steel Plate Surface Defect Detection System Based on Artificial Intelligence Machine Vision." Wireless Communications and Mobile Computing 2021 (April 27, 2021): 1–12. http://dx.doi.org/10.1155/2021/5553470.

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With the rapid development of visual inspection technology, computer technology, and image processing technology, machine vision technology has become more and more mature, and the role of quality inspection and control in the steel industry is becoming more and more obvious and important. Defects on the surface of the strip are a key factor affecting the quality inspection process. Its inspection plays an extremely important role in improving the final quality. For a long time, traditional manual inspection methods cannot meet actual production needs, so in-depth research on steel surface def

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23

Vigneron, Vincent, and Sylvie Lelandais. "Statistics for Image Processing." Pattern Recognition Letters 31, no. 14 (October 2010): 2191. http://dx.doi.org/10.1016/j.patrec.2010.07.003.

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Zhang, Na, Hongsen Xie, Jinjie Li, and Hong Chen. "Application of radar signal processing and image display algorithm based on computer hardware system in intelligence processing." Microprocessors and Microsystems 81 (March 2021): 103747. http://dx.doi.org/10.1016/j.micpro.2020.103747.

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Küçükdemirci, Melda, and Apostolos Sarris. "GPR Data Processing and Interpretation Based on Artificial Intelligence Approaches: Future Perspectives for Archaeological Prospection." Remote Sensing 14, no. 14 (July 13, 2022): 3377. http://dx.doi.org/10.3390/rs14143377.

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Ground penetrating radar (GPR) is a well-established technique used in archaeological prospection and it requires a number of specialized routines for signal and image processing to enhance the data acquired and lead towards a better interpretation of them. Computer-aided techniques have advanced the interpretation of GPR data, dealing with a wide range of operations aiming towards locating, imaging, and diagnosis/interpretation. This article will discuss the novel and recent applications of machine learning (ML) and deep learning (DL) techniques, under the artificial intelligence umbrella, fo

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26

Gong, Suning, Rakesh Kumar, and D. Kumutha. "Design of Lighting Intelligent Control System Based on OpenCV Image Processing Technology." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 29, Supp01 (March 26, 2021): 119–39. http://dx.doi.org/10.1142/s0218488521400079.

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The high growth of vehicular travel in urban areas, in particular, requires a traffic control system that optimizes traffic flow efficiency. Traffic congestion can also occur by large de-lays in Red Light etc. The delay in lighting is difficult to code and does not rely on real traffic density. It follows that traffic controls are simulated and configured to better meet this rising demand. So, in order to avoid the traffic control problem, the Adaptive Intelligent Traffic Light control system (AITLCS) has been proposed based on OpenCV and Image processing technique. The system proposed is desi

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27

Kumar, Subash. "Abstract PO-012: The concept of artificial intelligence against pancreatic cancer." Cancer Research 81, no. 22_Supplement (November 15, 2021): PO—012—PO—012. http://dx.doi.org/10.1158/1538-7445.panca21-po-012.

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Abstract Pancreatic cancer (PC) remains the fourth leading cause of cancer-related death in both men and women in the United States. Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Pancreatic ductal adenocarcinoma (PDAC) is on track to become the number 2 cancer killer in the United States within the next decade unless there is

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Arya, Vivek. "Robust Image Compression Algorithm using Discrete Fractional Cosine Transform." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 17 (January 5, 2022): 25–33. http://dx.doi.org/10.37394/23203.2022.17.3.

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The discrete fractional Fourier transform become paradigm in signal processing. This transform process the signal in joint time-frequency domain. The attractive and very important feature of DFrCT is an availability of extra degree of one free parameter that is provided by fractional orders and due to which optimization is possible. Less execution time and easy implementation are main advantages of proposed algorithm. The merit of effectiveness of proposed technique over existing technique is superior due to application of discrete fractional cosine transform by which higher compression ratio

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Viergever, Max A. "Volume image processing (VIP'93)." Pattern Recognition Letters 15, no. 5 (May 1994): 437–38. http://dx.doi.org/10.1016/0167-8655(94)90133-3.

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Suneetha, Akula, and E. Srinivasa Reddy. "Robust Gaussian Noise Detection and Removal in Color Images using Modified Fuzzy Set Filter." Journal of Intelligent Systems 30, no. 1 (August 15, 2020): 240–57. http://dx.doi.org/10.1515/jisys-2019-0211.

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Abstract In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges while removing noise. In this paper, a modified fuzzy set fi

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31

Ru, Lei, Bin Zhang, Jing Duan, and Guo Ru. "ANALYSIS OF BIOLO ARTIFICIAL NEURAL NETWORK IN PREDICTION OF AEROBIC EXERCISE INDEX BASED ON ALGORITHM." Revista Brasileira de Medicina do Esporte 27, no. 4 (August 2021): 367–71. http://dx.doi.org/10.1590/1517-8692202127042021_0126.

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ABSTRACT Objective: To study the relationship between aerobic activity and cardiac autonomic nerve activity by artificial neural network algorithm and biological image fusion; because of the artificial neural network model (ANN) problems, biological image processing technology is introduced based on ANN. Methods: An Ann under biological image intelligence algorithm is proposed, a classifier suitable for electrocardiograph (ECG) screening is designed, and an ECG signal screening system is successfully established. Moreover, the data set of normal recovered ECG signals of the subjects during the

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32

Yang, Wenxian, Radoslaw Zimroz, and Mayorkinos Papaelias. "Advances in Machine Condition Monitoring and Fault Diagnosis." Electronics 11, no. 10 (May 13, 2022): 1563. http://dx.doi.org/10.3390/electronics11101563.

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In the past few decades, with the great progress made in the field of computer technology, non-destructive testing, signal and image processing, and artificial intelligence, machine condition monitoring and fault diagnosis technology have also achieved great technological progress and played an active and important role in various industries to ensure the efficient and reliable operation of machines, lower the operation and maintenance costs, and improve the reliability and availability of large critical equipment [...]

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Iakovidis, Dimitris K., Melanie Ooi, Ye Chow Kuang, Serge Demidenko, Alexandr Shestakov, Vladimir Sinitsin, Manus Henry, et al. "Roadmap on signal processing for next generation measurement systems." Measurement Science and Technology 33, no. 1 (November 16, 2021): 012002. http://dx.doi.org/10.1088/1361-6501/ac2dbd.

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Abstract Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highligh

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Jia, Tao. "The Realization of FPGA + ARM-Based Image Matching." Applied Mechanics and Materials 220-223 (November 2012): 2799–802. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2799.

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The intelligent monitoring refers to the use of pattern recognition technology, digital signal processing, artificial intelligence theory and automatic control technology, and integrating video surveillance into the monitoring system, to enable the system become intelligent. The core technology for the system is the identification and matching of moving targets; and the fast & exact match detection of a moving target is the key step and technical basis for subsequent identification. Image-based matching has a wide range of applications in the field of industrial product testing, identifica

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Fukuda, Toshio, Yasuhisa Hasegawa, Yasuhiro Kawai, Shinsuke Sato, Zakarya Zyada, and Takayuki Matsuno. "GPR Signal Processing with Geography Adaptive Scanning using Vector Radar for Antipersonal Landmine Detection." International Journal of Advanced Robotic Systems 4, no. 2 (June 1, 2007): 22. http://dx.doi.org/10.5772/5696.

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Ground Penetrating Radar (GPR) is a promising sensor for landmine detection, however there are two major problems to overcome. One is the rough ground surface. The other problem is the distance between the antennas of GPR. It remains irremovable clutters on a sub-surface image output from GPR by first problem. Geography adaptive scanning is useful to image objects beneath rough ground surface. Second problem makes larger the nonlinearity of the relationship between the time for propagation and the depth of a buried object, imaging the small objects such as an antipersonnel landmine closer to t

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LI, YUN, BAO-LIANG LU, and TENG-FEI ZHANG. "COMBINING FEATURE SELECTION WITH EXTRACTION: UNSUPERVISED FEATURE SELECTION BASED ON PRINCIPAL COMPONENT ANALYSIS." International Journal on Artificial Intelligence Tools 18, no. 06 (December 2009): 883–904. http://dx.doi.org/10.1142/s0218213009000445.

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Principal components analysis (PCA) is a popular linear feature extractor, and widely used in signal processing, face recognition, etc. However, axes of the lower-dimensional space, i.e., principal components, are a set of new variables carrying no clear physical meanings. Thus we propose unsupervised feature selection algorithms based on eigenvectors analysis to identify critical original features for principal component. The presented algorithms are based on k-nearest neighbor rule to find the predominant row components and eight new measures are proposed to compute the correlation between r

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Basha, D. Khalandar, and T. Venkateswarlu. "Linear Regression Supporting Vector Machine and Hybrid LOG Filter-Based Image Restoration." Journal of Intelligent Systems 29, no. 1 (July 13, 2019): 1480–95. http://dx.doi.org/10.1515/jisys-2018-0492.

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Abstract The image restoration (IR) technique is a part of image processing to improve the quality of an image that is affected by noise and blur. Thus, IR is required to attain a better quality of image. In this paper, IR is performed using linear regression-based support vector machine (LR-SVM). This LR-SVM has two steps: training and testing. The training and testing stages have a distinct windowing process for extracting blocks from the images. The LR-SVM is trained through a block-by-block training sequence. The extracted block-by-block values of images are used to enhance the classificat

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Wang, Yuqing, and Yong Wang. "An Improved Biologically-Inspired Image Fusion Method." International Journal of Pattern Recognition and Artificial Intelligence 32, no. 08 (April 8, 2018): 1857004. http://dx.doi.org/10.1142/s0218001418570045.

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A biologically inspired image fusion mechanism is analyzed in this paper. A pseudo-color image fusion method is proposed based on the improvement of a traditional method. The proposed model describes the fusion process using several abstract definitions which correspond to the detailed behaviors of neurons. Firstly, the infrared image and visible image are respectively ON against enhanced and OFF against enhanced. Secondly, we feed back the enhanced visible images given by the ON-antagonism system to the active cells in the center-surrounding antagonism receptive field. The fused [Formula: see

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Qi, Liangtao, Lei Qiu, and Xiao Zhou. "Fault diagnosis method of mechanical power system based on image processing technology." International Journal of Advanced Robotic Systems 17, no. 2 (March 1, 2020): 172988142091409. http://dx.doi.org/10.1177/1729881420914093.

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Fault detection and diagnosis become one of today’s hot spots, which describes that image information is an important form of fault information, it can quickly through the image processing technique, and can accurately extract the characteristic signal. This article selects the color of the particle image, the integrated use of digital image processing, pattern recognition theory, the characteristic parameters of tribology knowledge, as well as the extraction, optimization, and digital; verifies the feasibility of iron spectrum of abrasive fault recognition, and provides a new efficient ferrog

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Liang, En-Hui, and Edward K. Wong. "Hierarchical algorithms for morphological image processing." Pattern Recognition 26, no. 4 (April 1993): 511–29. http://dx.doi.org/10.1016/0031-3203(93)90107-8.

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Qian, Kai, and Prabir Bhattacharya. "Binary image processing by polynomial approach." Pattern Recognition Letters 11, no. 6 (June 1990): 395–403. http://dx.doi.org/10.1016/0167-8655(90)90110-n.

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Tharmakulasingam, Mukunthan, Nouman S. Chaudhry, Manoharanehru Branavan, Wamadeva Balachandran, Aurore C. Poirier, Mohammed A. Rohaim, Muhammad Munir, Roberto M. La Ragione, and Anil Fernando. "An Artificial Intelligence-Assisted Portable Low-Cost Device for the Rapid Detection of SARS-CoV-2." Electronics 10, no. 17 (August 26, 2021): 2065. http://dx.doi.org/10.3390/electronics10172065.

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An artificial intelligence-assisted low-cost portable device for the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is presented here. This standalone temperature-controlled device houses tubes designed for conducting reverse transcription loop-mediated isothermal amplification (RT-LAMP) assays. Moreover, the device utilises tubes illuminated by LEDs, an in-built camera, and a small onboard computer with automated image acquisition and processing algorithms. This intelligent device significantly reduces the normal assay run time and removes the subjectivity ass

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Zheng, Zhiyan, Ruixuan He, Cuijun Lin, and Chunyu Huang. "Multimodal Magnetic Resonance Imaging to Diagnose Knee Osteoarthritis under Artificial Intelligence." Computational Intelligence and Neuroscience 2022 (June 23, 2022): 1–9. http://dx.doi.org/10.1155/2022/6488889.

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This work aimed to investigate the application value of the multimodal magnetic resonance imaging (MRI) algorithm based on the low-rank decomposition denoising (LRDD) in the diagnosis of knee osteoarthritis (KOA), so as to offer a better examination method in the clinic. Seventy-eight patients with KOA were selected as the research objects, and they all underwent T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), fat suppression T2WI (SE-T2WI), and fat saturation T2WI (FS-T2WI). All obtained images were processed by using the I-LRDD algorithm. According to the degree of articular cartilag

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Xu, Hui-hong, and Dong-yuan Ge. "A novel image edge smoothing method based on convolutional neural network." International Journal of Advanced Robotic Systems 17, no. 3 (May 1, 2020): 172988142092167. http://dx.doi.org/10.1177/1729881420921676.

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In the field of visual perception, the edges of images tend to be rich in effective visual stimuli, which contribute to the neural network’s understanding of various scenes. Image smoothing is an image processing method used to highlight the wide area, low-frequency components, main part of the image or to suppress image noise and high-frequency interference components, which could make the image’s brightness smooth and gradual, reduce the abrupt gradient, and improve the image quality. At present, there are still problems such as easy blurring of the edges of the image, poor overall smoothing

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DOUGHERTY, EDWARD R., and CHARLES R. GIARDINA. "MORPHOLOGY ON UMBRA MATRICES." International Journal of Pattern Recognition and Artificial Intelligence 02, no. 02 (June 1988): 367–85. http://dx.doi.org/10.1142/s0218001488000224.

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The umbra transform serves as a connection between gray-scale morphology and the classical two-valued morphology of G. Matheron and H. Hadwiger. From a general set-theoretic perspective, the umbra transform of an image (or signal) results in an infinite set, even in the discrete case. By employing bound matrix image representation it is possible to represent the umbra by a finite data structure, the result being an approach that is both intuitive and computational. Moreover, the method is essentially dimensionally independent and thus applies to both morphological image and signal processing.

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Jiang, Fangyun, Xiaoping Fu, Kai Kuang, and Dan Fan. "Artificial Intelligence Algorithm-Based Differential Diagnosis of Crohn’s Disease and Ulcerative Colitis by CT Image." Computational and Mathematical Methods in Medicine 2022 (April 4, 2022): 1–12. http://dx.doi.org/10.1155/2022/3871994.

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The aim of this study was to investigate the effect of low-dose CT enterography (CTE) based on modified guided image filtering (GIF) algorithm in the differential diagnosis of ulcerative colitis (UC) and Crohn’s disease (CD). Methods. One hundred and twenty patients with suspected diagnosis of IBD were studied. They were randomly divided into control group (routine CT examination) and observation group (low-dose CTE examination based on improved GIF algorithm), with 60 cases in each group. Comprehensive diagnosis was used as the standard to assess the diagnostic effect. Results. (1) The peak s

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Tang, Jian, Wenxiu Yu, Guoxin Zhao, Xiangdong Jiao, and Xuepeng Ding. "Application of Bispectrum Dimensionality Reduction Method in Ultrasonic Echo Signal Processing." Journal of Advanced Computational Intelligence and Intelligent Informatics 26, no. 6 (November 20, 2022): 1053–60. http://dx.doi.org/10.20965/jaciii.2022.p1053.

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Processing ultrasonic echo signals to obtain high-precision residual thickness information of the pipeline wall is the key to nondestructive testing of corrosion of a long-distance pipeline. The traditional power spectrum estimation method assumes that an analyzed echo signal is Gaussian, and the useful information is insufficiently extracted, which leads to errors in the processing results. In this paper, to solve this problem, the bispectrum, which requires the least amount of computation in higher-order spectral estimation, is proposed to process an echo signal with a non-minimum phase and

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Li, Shutao, James T. Kwok, and Yaonan Wang. "Multifocus image fusion using artificial neural networks." Pattern Recognition Letters 23, no. 8 (June 2002): 985–97. http://dx.doi.org/10.1016/s0167-8655(02)00029-6.

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Latinović, Nikola, Ilija Popadić, Branko Tomić, Aleksandar Simić, Petar Milanović, Srećko Nijemčević, Miroslav Perić, and Mladen Veinović. "Signal Processing Platform for Long-Range Multi-Spectral Electro-Optical Systems." Sensors 22, no. 3 (February 8, 2022): 1294. http://dx.doi.org/10.3390/s22031294.

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In this paper, we present a hardware and software platform for signal processing (SPP) in long-range, multi-spectral, electro-optical systems (MSEOS). Such systems integrate various cameras such as lowlight color, medium or long-wave-infrared thermal and short-wave-infrared cameras together with other sensors such as laser range finders, radars, GPS receivers, etc. on rotational pan-tilt positioner platforms. An SPP is designed with the main goal to control all components of an MSEOS and execute complex signal processing algorithms such as video stabilization, artificial intelligence-based tar

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Várkonyi-Kóczy, Annamária R. "Special Issue on Selected Papers WISP'99." Journal of Advanced Computational Intelligence and Intelligent Informatics 5, no. 1 (January 20, 2001): 1. http://dx.doi.org/10.20965/jaciii.2001.p0001.

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Abstract (sommario):

Today's complex industrial and engineering systems - especially with the appearance of large-scale embedded and/or real-time systems - confront researchers and engineers with completely new challenges. Measurement and signal processing systems are involved in almost all kinds of activities in that field where control problems, system identification problems, industrial technologies, etc., are to be solved, i.e., when signals, parameters, or attributes must be measured, monitored, approximated, or determined somehow. In a large number of cases, traditional information processing tools and equip

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