Relevant bibliographies by topics / Computer vision technology

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Computer vision technology'

Author: Grafiati
Published: 11 December 2022
Last updated: 27 January 2023

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Journal articles on the topic "Computer vision technology"

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Ohta, Yuichi. "3D Image Media and Computer Vision -From CV as Robot Technology to CV as Media Technology-." Journal of Robotics and Mechatronics 9, no. 2 (April 20, 1997): 92–97. http://dx.doi.org/10.20965/jrm.1997.p0092.

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The possibility to apply the computer vision technology to the development of a new image medium is discussed. Computer vision has been studied as a sensor technology between the real world and computers. On the other hand, the computer graphics are the interface technology between the computers and human beings. The invention of ""3D photography"" based on the computer vision technology will realize a new 3D image medium which connects the real world and the human beings via computer. In such a framework, computer vision should be studied as a media technology rather than a robot technology.
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Manasi, Mohaney, and Sonal Chaudhary. "Computer Vision Technology using Gesture Recognition." International Journal of Computer Applications 179, no. 19 (February 15, 2018): 1–4. http://dx.doi.org/10.5120/ijca2018916320.

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Milella, A., G. Reina, and M. Foglia. "Computer vision technology for agricultural robotics." Sensor Review 26, no. 4 (October 2006): 290–300. http://dx.doi.org/10.1108/02602280610692006.

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Ramadoss, Janarthanan, J. Venkatesh, Shubham Joshi, Piyush Kumar Shukla, Sajjad Shaukat Jamal, Majid Altuwairiqi, and Basant Tiwari. "Computer Vision for Human-Computer Interaction Using Noninvasive Technology." Scientific Programming 2021 (November 3, 2021): 1–15. http://dx.doi.org/10.1155/2021/3902030.

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Computer vision is a significant component of human-computer interaction (HCI) processes in interactive control systems. In general, the interaction between humans and computers relies on the flexibility of the interactive visualization system. Electromyography (EMG) is a bioelectric signal used in HCI that can be captured noninvasively by placing electrodes on the human hand. Due to the impact of complex background, accurate recognition and analysis of human motion in real-time multitarget scenarios are considered challenging in HCI. Further, EMG signals of human hand motions are exceedingly nonlinear, and it is important to utilize a dynamic approach to address the noise problem in EMG signals. Hence, in this paper, the Optimized Noninvasive Human-Computer Interaction (ONIHCI) model has been proposed to predict human motion recognition. Average Intrinsic Mode Function (AIMF) has been used to reduce the noise factor in EMG signals. Furthermore, this paper introduces spatial thermographic imaging to overcome the conventional sensor problem, such as gesture recognition and human target identification in multitarget scenarios. The human motion behavior in spatial thermographic images is examined by target trajectory, and body movement kinematics is employed to classify human targets and objects. The experimental findings demonstrate that the proposed method reduces noise by 7.2% and improves accuracy by 97.2% in human motion recognition and human target identification.
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Mamrega, V. V. "COMPUTER VISION." SYNCHROINFO JOURNAL 8, no. 5 (2022): 7–11. http://dx.doi.org/10.36724/2664-066x-2022-8-5-7-11.

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This article explores the subject of computer vision systems – a technology that allows vehicles to identify, track, and also classify objects on the roadway. The objectives of the study are to consider the principle of operation of these automated systems, their advantages in comparison with modern road regulation, as well as the problems of implementation and development of these systems. The research was carried out on the basis of the analysis of information from open information resources. The statistics of accidents at work are presented, the high rates of which are due to large volumes of production and an outdated system for monitoring compliance with safety rules and the availability of personal protective equipment for employees. The scheme of interaction of the components of a computer vision system is considered, which will allow monitoring of events occurring in production during operation, monitoring the situation at the enterprise for the occurrence of a potentially dangerous situation for personnel and equipment, and, accordingly, this system will be able to prevent an emergency, as well as avoid personal injury by reacting even to minor deviations from operating parameters. The research was carried out on the basis of the study and analysis of materials published in open information sources.
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Niu, Xiang Jie, and Bin Lan. "The Agricultural Products Deterioration Recognition Based on Computer Vision." Applied Mechanics and Materials 602-605 (August 2014): 2027–30. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2027.

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The computer vision technology is an important branch of computer science and artificial intelligence which is regarded as a non-destructive testing technique in the field of agriculture with a broad application prospects. This paper introduces the application of the computer vision technology in the agricultural products deterioration recognition, builds foundations for the accurate measurement of the agricultural products quality with computer visions, and establish the relationship between the feature information and quality of the agricultural products. Meanwhile, this paper combined the computer vision technology with infrared, microwave, NMR techniques to extract and test the visual information of the internal quality of the agricultural products.
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Mery, D. "Computer vision technology for X-ray testing." Insight - Non-Destructive Testing and Condition Monitoring 56, no. 3 (March 1, 2014): 147–55. http://dx.doi.org/10.1784/insi.2014.56.3.147.

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Luo, Bo, Xudong Wang, and Zhiyuan Zhang. "Application of Computer Vision Technology in UAV." Journal of Physics: Conference Series 1881, no. 4 (April 1, 2021): 042052. http://dx.doi.org/10.1088/1742-6596/1881/4/042052.

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Yang, Zeping, and Ge Gao. "Audit Optimization Based on Computer Vision Technology." Journal of Computer and Communications 10, no. 10 (2022): 50–58. http://dx.doi.org/10.4236/jcc.2022.1010004.

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Floryanzia, Sydney, Preethi Ramesh, Madeline Mills, Sanjana Kulkarni, Grace Chen, Prashant Shah, and David Lavrich. "Disintegration testing augmented by computer Vision technology." International Journal of Pharmaceutics 619 (May 2022): 121668. http://dx.doi.org/10.1016/j.ijpharm.2022.121668.

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Dissertations / Theses on the topic "Computer vision technology"

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Johansson, Björn. "Multiscale Curvature Detection in Computer Vision." Licentiate thesis, Linköping University, Linköping University, Computer Vision, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54966.

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This thesis presents a new method for detection of complex curvatures such as corners, circles, and star patterns. The method is based on a second degree local polynomial model applied to a local orientation description in double angle representation. The theory of rotational symmetries is used to compute curvature responses from the parameters of the polynomial model. The responses are made more selective using a scheme of inhibition between different symmetry models. These symmetries can serve as feature points at a high abstraction level for use in hierarchical matching structures for 3D estimation, object recognition, image database search, etc.

A very efficient approximative algorithm for single and multiscale polynomial expansion is developed, which is used for detection of the complex curvatures in one or several scales. The algorithm is based on the simple observation that polynomial functions multiplied with a Gaussian function can be described in terms of partial derivatives of the Gaussian. The approximative polynomial expansion algorithm is evaluated in an experiment to estimate local orientation on 3D data, and the performance is comparable to previously tested algorithms which are more computationally expensive.

The curvature algorithm is demonstrated on natural images and in an object recognition experiment. Phase histograms based on the curvature features are developed and shown to be useful as an alternative compact image representation.

The importance of curvature is furthermore motivated by reviewing examples from biological and perceptual studies. The usefulness of local orientation information to detect curvature is also motivated by an experiment about learning a corner detector.

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Bårman, Håkan. "Hierarchical curvature estimation in computer vision." Doctoral thesis, Linköpings universitet, Bildbehandling, 1991. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54887.

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This thesis concerns the estimation and description of curvature for computer vision applications. Different types of multi-dimensional data are considered: images (2D); volumes (3D); time sequences of images (3D); and time sequences of volumes (4D). The methods are based on local Fourier domain models and use local operations such as filtering. A hierarchical approach is used. Firstly, the local orientation is estimated and represented with a vector field equivalent description. Secondly, the local curvature is estimated from the orientation description. The curvature algorithms are closely related to the orientation estimation algorithms and the methods as a whole give a unified approach to the estimation and description of orientation and curvature. In addition, the methodology avoids thresholding and premature decision making. Results on both synthetic and real world data are presented to illustrate the algorithms performance with respect to accuracy and noise insensitivity. Examples illustrating the use of the curvature estimates for tasks such as image enhancement are also included.
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Moe, Anders. "Passive Aircraft Altitude Estimation using Computer Vision." Licentiate thesis, Linköping University, Linköping University, Computer Vision, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-53415.

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This thesis presents a number of methods to estimate 3D structures with a single translating camera. The camera is assumed to be calibrated and to have a known translation and rotation.

Applications for aircraft altitude estimation and ground structure estimation ahead of the aircraft are discussed. The idea is to mount a camera on the aircraft and use the motion estimates obtained in the inertia navigation system. One reason for this arrangement is to make the aircraft more passive, in comparison to conventional radar based altitude estimation.

Two groups of methods are considered, optical flow based and region tracking based. Both groups have advantages and drawbacks.

Two methods to estimate the optical flow are presented. The accuracy of the estimated ground structure is increased by varying the temporal distance between the frames used in the optical flow estimation algorithms.

Four region tracking algorithms are presented. Two of them use canonical correlation and the other two are based on sum of squared difference and complex correlation respectively.

The depth estimates are then temporally filtered using weighted least squares or a Kalman filter.

A simple estimation of the computational complexity and memory requirements for the algorithms is presented to aid estimation of the hardware requirements.

Tests on real flight sequences are performed, showing that the aircraft altitude can be estimated with a good accuracy.

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Söderkvist, Oskar. "Computer Vision Classification of Leaves from Swedish Trees." Thesis, Linköping University, Linköping University, Computer Vision, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54366.

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The aim of this master thesis is to classify the tree class from an image of a leaf with a computer vision classiffication system. We compare different descriptors that will describe the leaves different features. We will also look at different classiffication models and combine them with the descriptors to build a system hat could classify the different tree classes.

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Johansson, Björn. "Low Level Operations and Learning in Computer Vision." Doctoral thesis, Linköpings universitet, Bildbehandling, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-24005.

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This thesis presents some concepts and methods for low level computer vision and learning, with object recognition as the primary application. An efficient method for detection of local rotational symmetries in images is presented. Rotational symmetries include circle patterns, star patterns, and certain high curvature patterns. The method for detection of these patterns is based on local moments computed on a local orientation description in double angle representation, which makes the detection invariant to the sign of the local direction vectors. Some methods are also suggested to increase the selectivity of the detection method. The symmetries can serve as feature descriptors and interest points for use in hierarchical matching structures for object recognition and related problems. A view-based method for 3D object recognition and estimation of object pose from a single image is also presented. The method is based on simple feature vector matching and clustering. Local orientation regions computed at interest points are used as features for matching. The regions are computed such that they are invariant to translation, rotation, and locally invariant to scale. Each match casts a vote on a certain object pose, rotation, scale, and position, and a joint estimate is found by a clustering procedure. The method is demonstrated on a number of real images and the region features are compared with the SIFT descriptor, which is another standard region feature for the same application. Finally, a new associative network is presented which applies the channel representation for both input and output data. This representation is sparse and monopolar, and is a simple yet powerful representation of scalars and vectors. It is especially suited for representation of several values simultaneously, a property that is inherited by the network and something which is useful in many computer vision problems. The chosen representation enables us to use a simple linear model for non-linear mappings. The linear model parameters are found by solving a least squares problem with a non-negative constraint, which gives a sparse regularized solution.
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Klomark, Marcus. "Occupant Detection using Computer Vision." Thesis, Linköping University, Linköping University, Computer Vision, 2000. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54363.

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The purpose of this master’s thesis was to study the possibility to use computer vision methods to detect and classify objects in the front passenger seat in a car. This work presents different approaches to solve this problem and evaluates the usefulness of each technique. The classification information should later be used to modulate the speed and the force of the airbag, to be able to provide each occupant with optimal protection and safety.

This work shows that computer vision has a great potential in order to provide data, which may be used to perform reliable occupant classification. Future choice of method to use depends on many factors, for example costs and requirements on the system from laws and car manufacturers. Further, evaluation and tests of the methods in this thesis, other methods, the ABE approach and post-processing of the results should also be made before a reliable classification algorithm may be written.

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Fang, Jian. "Optical Imaging and Computer Vision Technology for Corn Quality Measurement." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/theses/733.

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The official U.S. standards for corn have been available for almost one hundred years. Corn grading system has been gradually updated over the years. In this thesis, we investigated a fast corn grading system, which includes the mechanical part and the computer recognition part. The mechanical system can deliver the corn kernels onto the display plate. For the computer recognition algorithms, we extracted common features from each corn kernel, and classified them to measure the grain quality.
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Andersson, Mats T. "Controllable Multi-dimensional Filters and Models in Low-Level Computer Vision." Doctoral thesis, Linköpings universitet, Bildbehandling, 1992. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54340.

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This thesis concerns robust estimation of low-level features for use in computer vision systems. The presentation consists of two parts. The first part deals with controllable filters and models. A basis filter set is introduced which supports a computationally efficient synthesis of filters in arbitrary orientations. In contrast to many earlier methods, this approach allows the use of more complex models at an early stage of the processing. A new algorithm for robust estimation of orientation is presented. The algorithm is based on synthesized quadrature responses and supports the simultaneous representation and individual averaging of multiple events. These models are then extended to include estimation and representation of more complex image primitives such as as line ends, T-junctions, crossing lines and curvature. The proposed models are based on symmetry properties in the Fourier domain as well as in the spatial plane and the feature extraction is performed by applying the original basis filters directly on the grey-level image. The basis filters and interpolation scheme are finally generalized to allow synthesis of 3-D filters. The performance of the proposed models and algorithms is demonstrated using test images of both synthetic and real world data. The second part of the thesis concerns an image feature representation adapted for a robust analogue implementation. A possible use for this approach is in analogue VLSI or corresponding analogue hardware adapted for neural networks. The methods are based on projections of quadrature filter responses and mutual inhibition of magnitude signals.
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Möller, Sebastian. "Image Segmentation and Target Tracking using Computer Vision." Thesis, Linköpings universitet, Datorseende, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-68061.

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In this master thesis the possibility of detecting and tracking objects in multispectral infrared video sequences is investigated. The current method  with fix-sized rectangles have significant disadvantages. These disadvantages will be solved using image segmentation to estimate the shape of the object. The result of the image segmentation is used to determine the infrared contrast of the object. Our results show how some objects will give very good segmentation, tracking as well as shape detection. The objects that perform best are the flares and countermeasures. But especially helicopters seen from the side, with significant movements, is better detected with our method. The motion of the object is very important since movement is the main component in successful shape detection. This is so because helicopters are much colder than flares and engines. Detecting the presence and position of moving objects is easier and can be done quite successfully even with helicopters. But using structure tensors we can also detect the presence and estimate the position for stationary objects.
I detta examensarbete undersöks möjligheterna att detektera och spåra intressanta objekt i multispektrala infraröda videosekvenser. Den nuvarande metoden, som använder sig av rektanglar med fix storlek, har sina nackdelar. Dessa nackdelar kommer att lösas med hjälp av bildsegmentering för att uppskatta formen på önskade mål.Utöver detektering och spårning försöker vi också att hitta formen och konturen för intressanta objekt för att kunna använda den exaktare passformen vid kontrastberäkningar. Denna framsegmenterade kontur ersätter de gamla fixa rektanglarna som använts tidigare för att beräkna intensitetskontrasten för objekt i de infraröda våglängderna. Resultaten som presenteras visar att det för vissa objekt, som motmedel och facklor, är lättare att få fram en bra kontur samt målföljning än vad det är med helikoptrar, som var en annan önskad måltyp. De svårigheter som uppkommer med helikoptrar beror till stor del på att de är mycket svalare vilket gör att delar av helikoptern kan helt döljas i bruset från bildsensorn. För att kompensera för detta används metoder som utgår ifrån att objektet rör sig mycket i videon så att rörelsen kan användas som detekteringsparameter. Detta ger bra resultat för de videosekvenser där målet rör sig mycket i förhållande till sin storlek.
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Lindvall, Victor. "A Computer Vision-Based Approach for Automated Inspection of Cable Connections." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-448446.

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The goal of the project was to develop an algorithm based on a Convolutional NeuralNetwork(CNN) for automatically detecting exposed metal components on coaxialcable connections, a.k.a. the detector. We show that the performance of such a CNN trained to identify bad weatherproofings can be improved by applying an image post processing technique. This post processing technique utilizes specular features as an advantage when predicting exposed metal components. Such specular features are notorious for posing problems in computer vision algorithms and therefore typically removed. The results achieved by applying the stand alone detector, without post processing, are compared with the image post processing approach to highlight the benefits of implementing such an algorithm.
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Books on the topic "Computer vision technology"

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López, Antonio M., Atsushi Imiya, Tomas Pajdla, and Jose M. Álvarez. Computer Vision in Vehicle Technology. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781118868065.

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Lampert, Christoph H. Kernel methods in computer vision. Hanover, MA: Now Publishers, Inc., 2009.

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IEEE International Conference on Advances in Computer Vision and Information Technology (2nd 2009 Aurangabad, India). Computer vision and information technology: Advances and applications. Edited by Kale K. V, Mehrotra S. C, Manza R. R, Institute of Electrical and Electronics Engineers. Bombay Section, and Dr. Babasaheb Ambedkar Marathwada University. Dept. of Computer Science and Information Technology. New Delhi: I.K. International Pub. House, 2010.

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Machine vision: A practical technology for advanced image processing. New York: Gordon and Breach Science Publishers, 1989.

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Martens, Jean-Bernard. Image Technology Design: A Perceptual Approach. Boston, MA: Springer US, 2003.

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Nihon Hōsō Kyōkai. Hōsō Gijutsu Kenkyūjo. High Definition Television: Hi-Vision Technology. Boston, MA: Springer US, 1993.

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1950-, MacDonald L. W., and Luo Ronnier, eds. Colour imaging: Vision and technology. Chichester, England: John Wiley, 1999.

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Hans, Knutsson, ed. Signal processing for computer vision. Dordrecht: Kluwer Academic Publishers, 1995.

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F, Bowman Charles, ed. Wisdom of the gurus: A vision for object technology. New York: SIGS Books & Multimedia, 1996.

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Caelli, Terry, Bai Xiao, and Jun Zhou. Computer vision and pattern recognition in environmental informatics. Hershey, PA: Information Science Reference, an imprint of IG Global, 2016.

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Book chapters on the topic "Computer vision technology"

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Baca, Arnold. "Computer Vision." In The Use of Applied Technology in Team Sport, 219–29. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003157007-21.

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Klette, Reinhard. "Computer Vision in Vehicles." In Computer Vision in Vehicle Technology, 1–23. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781118868065.ch1.

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Fraundorfer, Friedrich. "Computer Vision for MAVs." In Computer Vision in Vehicle Technology, 55–74. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781118868065.ch3.

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Chen, Quansheng, Hao Lin, and Jiewen Zhao. "Computer Vision Technology in Food." In Advanced Nondestructive Detection Technologies in Food, 91–126. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3360-7_4.

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Singh, Akanksha Krishna, Mausami, and Smita Kulkarni. "Attendance Monitoring Using Computer Vision." In Information and Communication Technology for Intelligent Systems, 725–32. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7078-0_72.

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Warwick, Kevin, and Mark Gasson. "Practical Interface Experiments with Implant Technology." In Computer Vision in Human-Computer Interaction, 7–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24837-8_2.

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Parraga, C. Alejandro, and Arash Akbarinia. "Color Name Applications in Computer Vision." In Encyclopedia of Color Science and Technology, 1–7. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-642-27851-8_404-1.

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Montegranario, Hebert, and Jairo Espinosa. "3D Data in Computer Vision and Technology." In Variational Regularization of 3D Data, 1–4. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0533-1_1.

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Burger, Wilhelm, and Matthew J. Barth. "Virtual Reality for Enhanced Computer Vision." In IFIP Advances in Information and Communication Technology, 247–57. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-0-387-34904-6_19.

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Namdari, Himan, Devak Nanda, and Xiaohui Yuan. "Progress in Computer Vision: Object Recognition." In Educational Communications and Technology: Issues and Innovations, 75–82. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84729-6_5.

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Conference papers on the topic "Computer vision technology"

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"Computer imaging and vision." In 2013 IEEE International Conference on Industrial Technology (ICIT 2013). IEEE, 2013. http://dx.doi.org/10.1109/icit.2013.6505960.

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Tao, Xueheng, Hongjie Li, Jinshi Lu, and Xuejun Wang. "Computer Vision Technology for Seafood Quality Evaluation." In 2012 International Conference on Computer Science and Service System (CSSS). IEEE, 2012. http://dx.doi.org/10.1109/csss.2012.470.

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Hou, Guangqi, Fei Liu, and Zhenan Sun. "Computer vision research with new imaging technology." In Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), edited by Tianxu Zhang and Jianguo Liu. SPIE, 2015. http://dx.doi.org/10.1117/12.2205630.

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Zeng, Jiexian, Yonglong Yu, and Bo Tian. "Landslide monitoring based on computer vision technology." In 2014 International Conference on Information Science, Electronics and Electrical Engineering (ISEEE). IEEE, 2014. http://dx.doi.org/10.1109/infoseee.2014.6948190.

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Morgachev, Vadim Vladislavovich. "Computer vision in children's sport robotized technology." In VII International applied research conference, chair Grigoriy Alekseevich Vorobyev. TSNS Interaktiv Plus, 2016. http://dx.doi.org/10.21661/r-81068.

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Qiu, Jin, Jian Liu, and Yunyi Shen. "Computer Vision Technology Based on Deep Learning." In 2021 IEEE 2nd International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA). IEEE, 2021. http://dx.doi.org/10.1109/iciba52610.2021.9687873.

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Lee, Hyung Min. "Bibigi (theremin based on computer-vision technology)." In SIGGRAPH07: Special Interest Group on Computer Graphics and Interactive Techniques Conference. New York, NY, USA: ACM, 2007. http://dx.doi.org/10.1145/1280120.1280141.

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Bi, Jiarui, Zengliang Zhu, and Qinglong Meng. "Transformer in Computer Vision." In 2021 IEEE International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI). IEEE, 2021. http://dx.doi.org/10.1109/cei52496.2021.9574462.

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C R, Praveen Khanna. "Automized Driver Personalization using Computer Vision." In Symposium on International Automotive Technology. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2021. http://dx.doi.org/10.4271/2021-26-0032.

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Wan, Heng, Yuewei Pan, Wenbo Chen, and Jiaqi Li. "Computer vision research based on OpenCV." In International Conference on Communication Technology. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/icct131612.

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Reports on the topic "Computer vision technology"

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Skouson, Mark B. How the Air Force Should Stay Engaged in Computer Vision Technology Development. Fort Belvoir, VA: Defense Technical Information Center, April 2007. http://dx.doi.org/10.21236/ada497741.

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Zorzetti, Silvia. Computer vision technology for the alignment monitoring of the prototype SSR1 cryomodule. Office of Scientific and Technical Information (OSTI), January 2020. http://dx.doi.org/10.2172/1615352.

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Velázquez López, Noé. Working Paper PUEAA No. 7. Development of a farm robot (Voltan). Universidad Nacional Autónoma de México, Programa Universitario de Estudios sobre Asia y África, 2022. http://dx.doi.org/10.22201/pueaa.005r.2022.

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Over the last century, agriculture has evolved from a labor-intensive industry to one that uses mechanized, high-powered production systems. The introduction of robotic technology in agriculture could be a new step towards labor productivity. By mimicking or extending human skills, robots overcome critical human limitations, including the ability to operate in harsh agricultural environments. In this context, in 2014 the development of the first agricultural robot in Mexico (“Voltan”) began at Chapingo Autonomous University. The research’s objective was to develop an autonomous multitasking vehicle for agricultural work. As a result of this development, a novel suspension system was created. In addition, autonomous navigation between crop rows was achieved through computer vision, allowing crop monitoring, fertilizer application and, in general, pest and disease control.
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Blok, Pieter M., and Antonius P. M. Tielen. Ontwikkeling en validatie van computer vision technologie ten behoeve van een broccoli oogstrobot. Wageningen: Stichting Wageningen Research, Wageningen Plant Research, Business unit Agrosysteemkunde, 2018. http://dx.doi.org/10.18174/448976.

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Тарасова, Олена Юріївна, and Ірина Сергіївна Мінтій. Web application for facial wrinkle recognition. Кривий Ріг, КДПУ, 2022. http://dx.doi.org/10.31812/123456789/7012.

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Facial recognition technology is named one of the main trends of recent years. It’s wide range of applications, such as access control, biometrics, video surveillance and many other interactive humanmachine systems. Facial landmarks can be described as key characteristics of the human face. Commonly found landmarks are, for example, eyes, nose or mouth corners. Analyzing these key points is useful for a variety of computer vision use cases, including biometrics, face tracking, or emotion detection. Different methods produce different facial landmarks. Some methods use only basic facial landmarks, while others bring out more detail. We use 68 facial markup, which is a common format for many datasets. Cloud computing creates all the necessary conditions for the successful implementation of even the most complex tasks. We created a web application using the Django framework, Python language, OpenCv and Dlib libraries to recognize faces in the image. The purpose of our work is to create a software system for face recognition in the photo and identify wrinkles on the face. The algorithm for determining the presence and location of various types of wrinkles and determining their geometric determination on the face is programmed.
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