Bücher zum Thema „Object detection in images“
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Bogusław Cyganek. Object Detection and Recognition in Digital Images. Oxford, UK: John Wiley & Sons Ltd, 2013. http://dx.doi.org/10.1002/9781118618387.
Der volle Inhalt der QuelleLee, Chin-Hwa. Similarity counting architecture for object detection. Monterey, California: Naval Postgraduate School, 1986.
Den vollen Inhalt der Quelle findenGeometric constraints for object detection and delineation. Boston: Kluwer Academic Publishers, 2000.
Den vollen Inhalt der Quelle findenWosnitza, Matthias Werner. High precision 1024-point FFT processor for 2D object detection. Hartung-Gorre: Konstanz, 1999.
Den vollen Inhalt der Quelle findenShaikh, Soharab Hossain, Khalid Saeed und Nabendu Chaki. Moving Object Detection Using Background Subtraction. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07386-6.
Der volle Inhalt der QuelleGoulermas, John. Hough transform techniques for circular object detection. Manchester: UMIST, 1996.
Den vollen Inhalt der Quelle findenJiang, Xiaoyue, Abdenour Hadid, Yanwei Pang, Eric Granger und Xiaoyi Feng, Hrsg. Deep Learning in Object Detection and Recognition. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-10-5152-4.
Der volle Inhalt der QuelleShufelt, Jefferey. Geometric Constraints for Object Detection and Delineation. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-5273-4.
Der volle Inhalt der QuelleNtalias, A. Automated flaw detection in textile images. Manchester: UMIST, 1995.
Den vollen Inhalt der Quelle findenSuk, Minsoo. Three-Dimensional Object Recognition from Range Images. Tokyo: Springer Japan, 1992.
Den vollen Inhalt der Quelle findenM, Bhandarkar S., Hrsg. Three-dimensional object recognition from range images. Tokyo: Springer-Verlag, 1992.
Den vollen Inhalt der Quelle findenSuk, Minsoo, und Suchendra M. Bhandarkar. Three-Dimensional Object Recognition from Range Images. Tokyo: Springer Japan, 1992. http://dx.doi.org/10.1007/978-4-431-68213-4.
Der volle Inhalt der QuelleAmit, Yali. 2D object detection and recognition: Models, algorithms, and networks. Cambridge, Mass: MIT Press, 2002.
Den vollen Inhalt der Quelle findenHighton, Scott. Virtual reality photography: Creating panoramic and object images. San Carlos, CA: Virtual Reality Photography, 2010.
Den vollen Inhalt der Quelle findenKarasulu, Bahadir. Performance Evaluation Software: Moving Object Detection and Tracking in Videos. New York, NY: Springer New York, 2013.
Den vollen Inhalt der Quelle findenKrivokapić, Natalija. Control mechanisms in distributed object bases: Synchronization, deadlock detection, migration. Sankt Augustin: Infix, 1999.
Den vollen Inhalt der Quelle findenArchibald, Colin. Witness, a system for object recognition using range images. Ottawa: National Research Council Canada, Division of Electrical Engineering, 1986.
Den vollen Inhalt der Quelle findenLowe, David G. Three-dimensional object recognition from single two-dimensional images. New York: Courant Institute of Mathematical Sciences, New York University, 1986.
Den vollen Inhalt der Quelle findenChen, Datong. Text detection and recognition in images and video sequences. Lausanne: EPFL, 2003.
Den vollen Inhalt der Quelle findenNunes Kehl, Thiago, Viviane Todt, Maurício Roberto Veronez und Silvio Cesar Cazella. Real time deforestation detection using ANN and Satellite images. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15741-2.
Der volle Inhalt der QuelleAndroutsos, Peter Panagiotis. Automatic structure and fault detection of semiconductor micrograph images. Ottawa: National Library of Canada, 1999.
Den vollen Inhalt der Quelle findenFrintrop, Simone. VOCUS: A Visual Attention System for Object Detection and Goal-Directed Search. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11682110.
Der volle Inhalt der QuelleLemmens, Mathias Johannes Peter Maria. Structure-based edge detection: Delineation of boundaries in aerial and space images. Delft, Netherlands: Delft University Press, 1996.
Den vollen Inhalt der Quelle findenNASA International Near-Earth-Object Detection Workshop (1992 San Juan Capistrano Research Institute, etc.). The spaceguard survey: Report of the NASA International Near-Earth-Object Detection Workshop, January 25 1992. Pasadena, Calif: NASA, Jet Propulsion Laboratory, California Institute of Technology ; reproduced by NTIS, 1992.
Den vollen Inhalt der Quelle findenCavanillas, Juan A. Aguilar. The role of color and false color in object recognition with degraded and non-degraded images. Monterey, Calif: Naval Postgraduate School, 1999.
Den vollen Inhalt der Quelle findenSafronov, A. N. Recovery of multi-chromatic distorted images of unknown space object by vector projecting onto convex sets. Moscow: Dorodnicyn computing centre of the Russian Academy of Sciences, 2006.
Den vollen Inhalt der Quelle findenA hierarchical object-based approach for urban land-use classification from remote sensing data. Enschede, Netherlands: ITC, 2003.
Den vollen Inhalt der Quelle findenHealey, Anthony J. Sonar signal acquisition and processing for identification and classification of ship hull fouling. Monterey, Calif: Naval Postgraduate School, 1993.
Den vollen Inhalt der Quelle finden1946-, Drury S. A., Hrsg. Images of the earth: A guide to remote sensing. 2. Aufl. Oxford [England]: Oxford University Press, 1998.
Den vollen Inhalt der Quelle findenBoom, Michael. The Amiga: Images, sounds, and animation on the Commodore Amiga. Redmond, Wash: Microsoft Press, 1986.
Den vollen Inhalt der Quelle findenCyganek, Boguslaw. Object Detection and Recognition in Digital Images: Theory and Practice. Wiley & Sons, Incorporated, John, 2013.
Den vollen Inhalt der Quelle findenCyganek, Boguslaw. Object Detection and Recognition in Digital Images: Theory and Practice. Wiley & Sons, Limited, John, 2013.
Den vollen Inhalt der Quelle findenJun, Shen, Pankanti Sharath, Wang Runsheng, Society of Photo-optical Instrumentation Engineers., Hua zhong gong xue yuan., Université de Bordeaux III, Guo jia zi ran ke xue ji jin wei yuan hui (China) und China Jiao yu bu, Hrsg. Object detection, classification, and tracking technologies: 22-24 October 2001, Wuhan, China. Bellingham, Wash., USA: SPIE, 2001.
Den vollen Inhalt der Quelle findenPeters, James F. Foundations of Computer Vision: Computational Geometry, Visual Image Structures and Object Shape Detection. Springer, 2018.
Den vollen Inhalt der Quelle findenYuan-Liang, Tang, Devadiga Sadashiva, United States. National Aeronautics and Space Administration., Pennsylvania State University. Dept. of Electrical and Computer Engineering. und Langley Research Center, Hrsg. A model-based approach for detection of objects in low resolution passive millimeter wave images. University Park, PA: Dept. of Electrical and Computer Engineering, The Pennsylvania State University, 1993.
Den vollen Inhalt der Quelle findenSingh, Himanshu. Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python. Apress, 2019.
Den vollen Inhalt der Quelle findenAmit, Yali. 2D Object Detection and Recognition. The MIT Press, 2002. http://dx.doi.org/10.7551/mitpress/1006.001.0001.
Der volle Inhalt der QuelleK, Jurgen Ronald, und Society of Automotive Engineers, Hrsg. Object detection, collision warning & avoidance systems. Warrendale, PA: SAE International, 2007.
Den vollen Inhalt der Quelle findenJurgen, Ronald K. Object Detection, Collision Warning and Avoidance Systems. SAE International, 2007.
Den vollen Inhalt der Quelle findenJiang, Xiaoyue, Eric Granger, Abdenour Hadid, Yanwei Pang und Xiaoyi Feng. Deep Learning in Object Detection and Recognition. Springer, 2019.
Den vollen Inhalt der Quelle findenJiang, Xiaoyue, Abdenour Hadid und Yanwei Pang. Deep Learning in Object Detection and Recognition. Springer, 2019.
Den vollen Inhalt der Quelle findenK, Jurgen Ronald, und Society of Automotive Engineers, Hrsg. Object detection, collision warning, and avoidance systems. Warrendale, PA: Society of Automotive Engineers, 1998.
Den vollen Inhalt der Quelle findenJiang, Xiaoyue, Eric Granger, Abdenour Hadid, Yanwei Pang und Xiaoyi Feng. Deep Learning in Object Detection and Recognition. Springer, 2021.
Den vollen Inhalt der Quelle findenRemote Sensing for Target Object Detection and Identification. MDPI, 2020. http://dx.doi.org/10.3390/books978-3-03928-333-0.
Der volle Inhalt der Quelle1949-, Kasturi Rangachar, und United States. National Aeronautics and Space Administration., Hrsg. Algorithms for detection of objects in image sequences captured from an airborne imaging system. University Park, PA: Dept. of Computer Science and Engineering, Pennsylvania State University, 1995.
Den vollen Inhalt der Quelle findenYuan-Liang, Tang, Devadiga Sadashiva und United States. National Aeronautics and Space Administration., Hrsg. A model-based approach for detection of objects in low resolution passive millimeter wave images: An interim report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", for the period January 24, 1992 to January 23, 1993. University Park PA: Dept. of Electrical and COmputer Engineering, Pennsylvania State University, 1993.
Den vollen Inhalt der Quelle findenYuan-Liang, Tang, Devadiga Sadashiva und United States. National Aeronautics and Space Administration., Hrsg. A model-based approach for detection of objects in low resolution passive millimeter wave images: An interim report for NASA grant NAG-1-1371, "analysis of image sequences from sensors for restricted visibility operations", for the period January 24, 1992 to January 23, 1993. University Park PA: Dept. of Electrical and COmputer Engineering, Pennsylvania State University, 1993.
Den vollen Inhalt der Quelle finden2D Object Detection and Recognition: Models, Algorithms, and Networks. The MIT Press, 2002.
Den vollen Inhalt der Quelle findenMichelucci, Umberto. Advanced Applied Deep Learning: Convolutional Neural Networks and Object Detection. Apress, 2019.
Den vollen Inhalt der Quelle findenMangalindan, Diane Marie J. Children's detection and use of cues to infer object displacement. 2007.
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