Relevant bibliographies by topics / Computer vision – Computer programs

Contents

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

Academic literature on the topic 'Computer vision – Computer programs'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Computer vision – Computer programs"

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Eladawi, A. E., E. S. Gadelmawla, I. M. Elewa, and A. A. Abdel-Shafy. "An application of computer vision for programming computer numerical control machines." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 217, no. 9 (2003): 1315–24. http://dx.doi.org/10.1243/095440503322420241.

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Generation of the part programs, or tool paths, for products to be manufactured by computer numerical control (CNC) machines is very important. Many methods have been used to produce part programs, ranging from manual calculations to computer aided design/ manufacturing (CAD/CAM) systems. This work introduces a new technique for generating the part programs of existing products using the latest technology of computer vision. The proposed vision system is applicable for two-dimensional vertical milling CNC machines and is calibrated to produce both metric and imperial dimensions. Two steps are
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Aniket Shinde, Bhanu Tekwani, Mandar Salvi, Shravan Kegade,. "CURSOR MANIPULATION WITH HAND RECOGNITION USING COMPUTER VISION." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (2021): 1455–56. http://dx.doi.org/10.17762/itii.v9i1.298.

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This paper aims to make a software program which will Track/Monitor your hand movement in front of the screen through a webcam and will move the cursor of the computing system with respect to your hand movement and can do certain fixed tasks like Right Click, Left Click, Scroll, Drag, Switch Between Programs, Go back, Forward, etc. This program will work in background and use convolutional Neural Networks Model (SSD) to convolve each and every video frame coming from input and at the end will classify the image into classes after further processing of the predicted class it will do necessary o
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Hartman, Amiel, and Vidya K. Nandikolla. "Human-Machine Interface for a Smart Wheelchair." Journal of Robotics 2019 (January 2, 2019): 1–11. http://dx.doi.org/10.1155/2019/4837058.

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The paper describes the integration of hardware and software with sensor technology and computer processing to develop the next generation intelligent wheelchair. The focus is a computer cluster design to test high performance computing for smart wheelchair operation and human interaction. The LabVIEW cluster is developed for real-time autonomous path planning and sensor data processing. Four small form factor computers are connected over a Gigabit Ethernet local area network to form the computer cluster. Autonomous programs are distributed across the cluster for increased task parallelism to
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Jomoah, Ibrahim M. "Work-Related Health Disorders among Saudi Computer Users." Scientific World Journal 2014 (2014): 1–27. http://dx.doi.org/10.1155/2014/723280.

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The present study was conducted to investigate the prevalence of musculoskeletal disorders and eye and vision complaints among the computer users of King Abdulaziz University (KAU), Saudi Arabian Airlines (SAUDIA), and Saudi Telecom Company (STC). Stratified random samples of the work stations and operators at each of the studied institutions were selected and the ergonomics of the work stations were assessed and the operators’ health complaints were investigated. The average ergonomic score of the studied work station at STC, KAU, and SAUDIA was 81.5%, 73.3%, and 70.3, respectively. Most of t
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Cubero, S., E. Moltó, A. Gutiérrez, et al. "Real-time inspection of fruit by computer vision on a mobile harvesting platform under field conditions." Progress in Agricultural Engineering Sciences 6, no. 1 (2010): 1–16. http://dx.doi.org/10.1556/progress.6.2010.1.

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The best alternative for reducing citrus production costs is mechanization. Machine vision is a reliable technology for the automatic inspection of fresh fruits and vegetables that can be adapted to harvesting machines. In these, fruits can be inspected before sending them to the packinghouse and machine vision provides important information for subsequent processing and avoids spending further resources in non-marketable fruit. The present work describes a computer vision system installed on a harvesting machine developed jointly by IVIA and a Spanish enterprise. In this machine, hand pickers
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Chen, I.-Hui, Shei-Chen Ho, Jun-Yang Chen, Yu-Shu Lin, and Miau-Bin Su. "Applying Computer Vision Technology to Triaxial Deformation Monitoring of Remedial Construction for a Landslide." International Journal of Sensors, Wireless Communications and Control 9, no. 4 (2019): 488–96. http://dx.doi.org/10.2174/2210327909666190208153757.

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Background & Objective: The paper explores a new instrument of computer vision to measure three-dimension deformation with an Internet of Things (IoT) system including Raspberry Pi, digital cameras and OpenCV programs in laboratory and field testing so as to monitor the potential deformation of a structure drainage well in a landslide. Methods: A chessboard pattern is detected in the image by the camera so that pixels of chessboard cornors can be recognized by OpenCV programs. X-direction, Y-direction and Z-distance changes can be casulated by the similar triangles relationship of camera p
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Pittenger, David J. "Perception Laboratory: A Computer Program to Demonstrate Perceptual Phenomena." Teaching of Psychology 23, no. 1 (1996): 46–48. http://dx.doi.org/10.1207/s15328023top2301_12.

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I developed an interactive computer program that allows one to demonstrate and experiment with various phenomena in visual perception using IBM-compatible computers. The program contains modules for demonstrating the color afterimage, the cafe illusion, additive color mixing and the opponent-process theory of color vision, the glowing axes illusion, the Hermann grid, the McCollough effect, the motion aftereffect, the neon illusion, and simultaneous contrast. The user has considerable control over the stimuli making up the image and can manipulate the variables that contribute to the perception
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Jamieson, Joan. "TRENDS IN COMPUTER-BASED SECOND LANGUAGE ASSESSMENT." Annual Review of Applied Linguistics 25 (March 2005): 228–42. http://dx.doi.org/10.1017/s0267190505000127.

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In the last 20 years, several authors have described the possible changes that computers may effect in language testing. Since ARAL's last review of general language testing trends (Clapham, 2000), authors in the Cambridge Language Assessment Series have offered various visions of how computer technology could alter the testing of second language skills. This chapter reflects these perspectives as it charts the paths recently taken in the field. Initial steps were made in the conversion of existing item types and constructs already known from paper-and- pencil testing into formats suitable for
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Zhang, Weini. "Research on Recognition Method of Basketball Goals Based on Image Analysis of Computer Vision." Journal of Sensors 2021 (September 20, 2021): 1–11. http://dx.doi.org/10.1155/2021/5269431.

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Moving target detection is involved in many engineering applications, but basketball has some difficulties because of the time-varying speed and uncertain path. The purpose of this paper is to use computer vision image analysis to identify the path and speed of a basketball goal, so as to meet the needs of recognition and achieve trajectory prediction. This research mainly discusses the basketball goal recognition method based on computer vision. In the research process, Kalman filter is used to improve the KCF tracking algorithm to track the basketball path. The algorithm of this research is
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Dorea, Joao R., Tiago Bresolin, Rafael E. P. Ferreira, and Luiz Gustavo R. Pereira. "383 Harnessing the Power of Computer Vision System to Improve Management Decisions in Livestock Operations." Journal of Animal Science 98, Supplement_4 (2020): 138–39. http://dx.doi.org/10.1093/jas/skaa278.255.

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Abstract In livestock operations, systematically monitoring animal body weight, biometric body measurements, animal behavior, feed bunk, and other complex phenotypes is unfeasible due to labor, costs, and animal stress. Applications of computer vision are growing in importance in livestock systems due to their ability to generate real-time, non-invasive, and accurate animal-level information. Such technology has emerged as a powerful tool to predict animal identification, body weight, biometric measurements, complex behavioral traits, and feed bunk score. However, the development of a computer
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Dissertations / Theses on the topic "Computer vision – Computer programs"

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Chiu, Kevin (Kevin Geeyoung). "Vision on tap : an online computer vision toolkit." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/67714.

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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student submitted PDF version of thesis.<br>Includes bibliographical references (p. 60-64).<br>In this thesis, we present an online toolkit, based on a combination of a Scratch-based programming environment and computer vision libraries, manifested as blocks within the environment, integrated with
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Zakaria, Marwan F. "An automated vision system using a fast 2-dimensional moment invariants algorithm /." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66244.

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Naik, Nikhil (Nikhil Deepak). "Visual urban sensing : understanding cities through computer vision." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/109656.

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Thesis: Ph. D., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 122-131).<br>This thesis introduces computer vision algorithms that harness street-level imagery to conduct automated surveys of the built environment and populations at an unprecedented resolution and scale. We introduce new tools for computing quantitative measures of urban appearance and urban change. First, we describe Streetscore, an algorithm that quantifies how safe a s
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Dittmar, George William. "Object Detection and Recognition in Natural Settings." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/926.

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Much research as of late has focused on biologically inspired vision models that are based on our understanding of how the visual cortex processes information. One prominent example of such a system is HMAX [17]. HMAX attempts to simulate the biological process for object recognition in cortex based on the model proposed by Hubel & Wiesel [10]. This thesis investigates the ability of an HMAX-like system (GLIMPSE [20]) to perform object-detection in cluttered natural scenes. I evaluate these results using the StreetScenes database from MIT [1, 8]. This thesis addresses three questions: (1) Can
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Driscoll, Michael T. "A machine vision system for capture and interpretation of an orchestra conductor's gestures." Link to electronic version, 1999. http://www.wpi.edu/Pubs/ETD/Available/etd-051199-142455/unrestricted/thesis.pdf.

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Thesis (M.S.)--Worcester Polytechnic Institute.<br>Keywords: color thresholding; video for Windows; center of mass calculation; contour extraction; area calculation; virtual orchestra; Broadway. Includes bibliographical references (leaves 62-63).
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Cai, Bill Yang. "Applications of deep learning and computer vision in large scale quantification of tree canopy cover and real-time estimation of street parking." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/122317.

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Thesis: S.M., Massachusetts Institute of Technology, Computation for Design and Optimization Program, 2018<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 73-77).<br>A modern city generates a large volume of digital information, especially in the form of unstructured image and video data. Recent advancements in deep learning techniques have enabled effective learning and estimation of high-level attributes and meaningful features from large digital datasets of images and videos. In my thesis, I explore the potential of applying deep learning to image and
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Kiang, Kai-Ming Mechanical &amp Manufacturing Engineering Faculty of Engineering UNSW. "Natural feature extraction as a front end for simultaneous localization and mapping." Awarded by:University of New South Wales. School of Mechanical and Manufacturing Engineering, 2006. http://handle.unsw.edu.au/1959.4/26960.

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This thesis is concerned with algorithms for finding natural features that are then used for simultaneous localisation and mapping, commonly known as SLAM in navigation theory. The task involves capturing raw sensory inputs, extracting features from these inputs and using the features for mapping and localising during navigation. The ability to extract natural features allows automatons such as robots to be sent to environments where no human beings have previously explored working in a way that is similar to how human beings understand and remember where they have been. In extracting natural
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McClure, Kerry S. "The use of object-oriented tools in the development of a pilot's vision simulation program to aid in the conceptual design of aircraft." Thesis, This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-07292009-090340/.

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Voils, Danny. "Scale Invariant Object Recognition Using Cortical Computational Models and a Robotic Platform." PDXScholar, 2012. https://pdxscholar.library.pdx.edu/open_access_etds/632.

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This paper proposes an end-to-end, scale invariant, visual object recognition system, composed of computational components that mimic the cortex in the brain. The system uses a two stage process. The first stage is a filter that extracts scale invariant features from the visual field. The second stage uses inference based spacio-temporal analysis of these features to identify objects in the visual field. The proposed model combines Numenta's Hierarchical Temporal Memory (HTM), with HMAX developed by MIT's Brain and Cognitive Science Department. While these two biologically inspired paradigms a
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Revell, James Duncan. "Computer vision elastography." Thesis, University of Bristol, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.412361.

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Books on the topic "Computer vision – Computer programs"

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Dawson-Howe, Kenneth. A practical introduction to computer vision with OpenCV. John Wiley & Sons., Inc., 2014.

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Corporation, Ontario Systems. User's guide to CT-Vision, version 8.0. Ontario Systems Corp., 1998.

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Fretwell, P. Linguistic definition of generic models in computer vision. HMSO, 1987.

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1959-, Dybkjær Laila, Minker Wolfgang, Neumann Heiko, Pieraccini Roberto, Weber Michael, and SpringerLink (Online service), eds. Perception in Multimodal Dialogue Systems: 4th IEEE Tutorial and Research Workshop on Perception and Interactive Technologies for Speech-Based Systems, PIT 2008, Kloster Irsee, Germany, June 16-18, 2008. Proceedings. Springer-Verlag Berlin Heidelberg, 2008.

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Vision & voice: Refining your vision in Adobe Photoshop lightroom. New Riders, 2011.

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Schumann, Michael. Turbo Vision toolbox. Abacus, 1992.

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Watson, Blake. Programming with Turbo vision. M&T Books, 1994.

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Scaling up machine learning: Parallel and distributed approaches. Cambridge University Press, 2011.

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T, Marshak Ronni, and Millikin Michael D, eds. Integrated desk-top environments: Symphony, Framework, Visi On, and DesQ. McGraw-Hill, 1985.

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Corrochano, Eduardo Bayro. Geometric computing: Or wavelet transforms, robot vision, learning, control and action. Springer, 2010.

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Book chapters on the topic "Computer vision – Computer programs"

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Wang, Shaofei, Alexander Ihler, Konrad Kording, and Julian Yarkony. "Accelerating Dynamic Programs via Nested Benders Decomposition with Application to Multi-Person Pose Estimation." In Computer Vision – ECCV 2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01264-9_40.

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Brahmbhatt, Samarth. "Embedded Computer Vision: Running OpenCV Programs on the Raspberry Pi." In Practical OpenCV. Apress, 2013. http://dx.doi.org/10.1007/978-1-4302-6080-6_11.

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Barragan, Luis Angel, and Armando Roy. "An empirical study of vision programs for data dependence analysis." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56891-3_65.

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Zhu, Zhihao, Zhan Xue, and Zejian Yuan. "Automatic Graphics Program Generation Using Attention-Based Hierarchical Decoder." In Computer Vision – ACCV 2018. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20876-9_12.

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Josiński, Henryk, Adam Świtoński, Karol Jędrasiak, Andrzej Polański, and Konrad Wojciechowski. "Matlab Based Interactive Simulation Program for 2D Multisegment Mechanical Systems." In Computer Vision and Graphics. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15910-7_15.

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Prabhu, Ameya, Philip H. S. Torr, and Puneet K. Dokania. "GDumb: A Simple Approach that Questions Our Progress in Continual Learning." In Computer Vision – ECCV 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58536-5_31.

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Belan, Peterson A., Robson A. G. de Macedo, and Sidnei A. de Araújo. "Computer Vision Approaches to Detect Bean Defects." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33904-3_31.

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Gallenbacher, Jens. "The Adventure of Computer Science." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98355-4_31.

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Williams, Linda J., Robin J. Prescott, and Mark Hartswood. "Computer-Aided Cancer Detection in the UK Breast Screening Programme." In Computational Imaging and Vision. Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5318-8_58.

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Burlina, P., N. Joshi, and N. M. Bressler. "AI-based AMD Analysis: A Review of Recent Progress." In Computer Vision – ACCV 2018 Workshops. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21074-8_25.

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Conference papers on the topic "Computer vision – Computer programs"

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Bihlmaier, Andreas, and Heinz Worn. "CVVisual: Interactive visual debugging of computer vision programs." In 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA). IEEE, 2015. http://dx.doi.org/10.1109/etfa.2015.7301408.

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Johnson, Justin, Bharath Hariharan, Laurens Van Der Maaten, et al. "Inferring and Executing Programs for Visual Reasoning." In 2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017. http://dx.doi.org/10.1109/iccv.2017.325.

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Parag, Toufiq, Claus Bahlmann, Vinay Shet, and Maneesh Singh. "A grammar for hierarchical object descriptions in logic programs." In 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR Workshops). IEEE, 2012. http://dx.doi.org/10.1109/cvprw.2012.6239171.

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Kharma, Nawwaf, Mohammad Ebne-Alian, and Louis Charbonneau. "Evolution of Programs for Segmentation of Microscopic Images." In 2015 12th Conference on Computer and Robot Vision (CRV). IEEE, 2015. http://dx.doi.org/10.1109/crv.2015.40.

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Puig, Xavier, Kevin Ra, Marko Boben, et al. "VirtualHome: Simulating Household Activities Via Programs." In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2018. http://dx.doi.org/10.1109/cvpr.2018.00886.

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Chin, Tat-Jun, Yang Heng Kee, Anders Eriksson, and Frank Neumann. "Guaranteed Outlier Removal with Mixed Integer Linear Programs." In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. http://dx.doi.org/10.1109/cvpr.2016.631.

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Eckstein, Wolfgang, and Carsten T. Steger. "Interactive data inspection and program development for computer vision." In Electronic Imaging: Science & Technology, edited by Georges G. Grinstein and Robert F. Erbacher. SPIE, 1996. http://dx.doi.org/10.1117/12.234677.

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Chang, Ning San. "SMV - A Computer Vision Program for Loading Surface Mount Components." In 29th Annual Technical Symposium, edited by Richard A. Brook and Michael J. W. Chen. SPIE, 1985. http://dx.doi.org/10.1117/12.966261.

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Yin, Fang-Fang, Maryellen L. Giger, Kunio Doi, Carl J. Vyborny, Robert A. Schmidt, and Charles E. Metz. "Computer vision system for the detection and characterization of masses for use in mammographic screening programs." In Midwest - DL tentative, edited by Rudolph P. Guzik, Hans E. Eppinger, Richard E. Gillespie, Mary K. Dubiel, and James E. Pearson. SPIE, 1991. http://dx.doi.org/10.1117/12.47733.

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"Program Committee." In 2017 Workshop of Computer Vision (WVC). IEEE, 2017. http://dx.doi.org/10.1109/wvc.2017.00007.

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Reports on the topic "Computer vision – Computer programs"

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Michalski, R. S., A. Rosenfeld, Y. Aloimonos, Z. Duric, and M. Maloof. Computer Vision through Learning. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada341212.

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Jones, J. (Computer vision and robotics). Office of Scientific and Technical Information (OSTI), 1989. http://dx.doi.org/10.2172/6860370.

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Poggio, Tomaso, and James Little. Parallel Algorithms for Computer Vision. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada203947.

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Rosenfeld, Azriel. Qualitative Methods in Computer Vision. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada264335.

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Waggett, Michael L. Night Vision Goggles Computer Based Training. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada398875.

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Fujiwara, Yoshimasa, Shree Nayer, and Katsushi Ikeuchi. Appearance Simulator for Computer Vision Research. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada240506.

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Berry, Nina M., and Teresa H. Ko. On computer vision in wireless sensor networks. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/919195.

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Campbell, Nancy, Glenn Osga, David Kellmeyer, Daniel Lulue, and Earl Williams. A Human-Computer Interface Vision for Naval Transformation. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada427415.

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Wright, John, Yi Ma, Julien Mairal, Guillermo Sapiro, Thomas Huang, and Shuicheng Yan. Sparse Representation for Computer Vision and Pattern Recognition. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada513248.

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Mahoney, John R. Reflections on a Strategic Vision for Computer Network Operations. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada526196.

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