Books on the topic 'Object detection in images'

Bogusław Cyganek. Object Detection and Recognition in Digital Images. Oxford, UK: John Wiley & Sons Ltd, 2013. http://dx.doi.org/10.1002/9781118618387.

Lee, Chin-Hwa. Similarity counting architecture for object detection. Monterey, California: Naval Postgraduate School, 1986.

Geometric constraints for object detection and delineation. Boston: Kluwer Academic Publishers, 2000.

Wosnitza, Matthias Werner. High precision 1024-point FFT processor for 2D object detection. Hartung-Gorre: Konstanz, 1999.

Shaikh, Soharab Hossain, Khalid Saeed, and Nabendu Chaki. Moving Object Detection Using Background Subtraction. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07386-6.

Goulermas, John. Hough transform techniques for circular object detection. Manchester: UMIST, 1996.

Jiang, Xiaoyue, Abdenour Hadid, Yanwei Pang, Eric Granger, and Xiaoyi Feng, eds. Deep Learning in Object Detection and Recognition. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-10-5152-4.

Shufelt, Jefferey. Geometric Constraints for Object Detection and Delineation. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-5273-4.

Ntalias, A. Automated flaw detection in textile images. Manchester: UMIST, 1995.

Suk, Minsoo. Three-Dimensional Object Recognition from Range Images. Tokyo: Springer Japan, 1992.

M, Bhandarkar S., ed. Three-dimensional object recognition from range images. Tokyo: Springer-Verlag, 1992.

Suk, Minsoo, and 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.

Amit, Yali. 2D object detection and recognition: Models, algorithms, and networks. Cambridge, Mass: MIT Press, 2002.

Highton, Scott. Virtual reality photography: Creating panoramic and object images. San Carlos, CA: Virtual Reality Photography, 2010.

Karasulu, Bahadir. Performance Evaluation Software: Moving Object Detection and Tracking in Videos. New York, NY: Springer New York, 2013.

Krivokapić, Natalija. Control mechanisms in distributed object bases: Synchronization, deadlock detection, migration. Sankt Augustin: Infix, 1999.

Archibald, Colin. Witness, a system for object recognition using range images. Ottawa: National Research Council Canada, Division of Electrical Engineering, 1986.

Lowe, David G. Three-dimensional object recognition from single two-dimensional images. New York: Courant Institute of Mathematical Sciences, New York University, 1986.

Chen, Datong. Text detection and recognition in images and video sequences. Lausanne: EPFL, 2003.

Nunes Kehl, Thiago, Viviane Todt, Maurício Roberto Veronez, and 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.

Androutsos, Peter Panagiotis. Automatic structure and fault detection of semiconductor micrograph images. Ottawa: National Library of Canada, 1999.

Frintrop, 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.

Lemmens, Mathias Johannes Peter Maria. Structure-based edge detection: Delineation of boundaries in aerial and space images. Delft, Netherlands: Delft University Press, 1996.

NASA 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.

Cavanillas, 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.

Safronov, 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.

A hierarchical object-based approach for urban land-use classification from remote sensing data. Enschede, Netherlands: ITC, 2003.

Healey, Anthony J. Sonar signal acquisition and processing for identification and classification of ship hull fouling. Monterey, Calif: Naval Postgraduate School, 1993.

1946-, Drury S. A., ed. Images of the earth: A guide to remote sensing. 2nd ed. Oxford [England]: Oxford University Press, 1998.

Boom, Michael. The Amiga: Images, sounds, and animation on the Commodore Amiga. Redmond, Wash: Microsoft Press, 1986.

Cyganek, Boguslaw. Object Detection and Recognition in Digital Images: Theory and Practice. Wiley & Sons, Incorporated, John, 2013.

Cyganek, Boguslaw. Object Detection and Recognition in Digital Images: Theory and Practice. Wiley & Sons, Limited, John, 2013.

Jun, 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), and China Jiao yu bu, eds. Object detection, classification, and tracking technologies: 22-24 October 2001, Wuhan, China. Bellingham, Wash., USA: SPIE, 2001.

Peters, James F. Foundations of Computer Vision: Computational Geometry, Visual Image Structures and Object Shape Detection. Springer, 2018.

Yuan-Liang, Tang, Devadiga Sadashiva, United States. National Aeronautics and Space Administration., Pennsylvania State University. Dept. of Electrical and Computer Engineering., and Langley Research Center, eds. 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.

Singh, Himanshu. Practical Machine Learning and Image Processing: For Facial Recognition, Object Detection, and Pattern Recognition Using Python. Apress, 2019.

Amit, Yali. 2D Object Detection and Recognition. The MIT Press, 2002. http://dx.doi.org/10.7551/mitpress/1006.001.0001.

K, Jurgen Ronald, and Society of Automotive Engineers, eds. Object detection, collision warning & avoidance systems. Warrendale, PA: SAE International, 2007.

Jurgen, Ronald K. Object Detection, Collision Warning and Avoidance Systems. SAE International, 2007.

Jiang, Xiaoyue, Eric Granger, Abdenour Hadid, Yanwei Pang, and Xiaoyi Feng. Deep Learning in Object Detection and Recognition. Springer, 2019.

Jiang, Xiaoyue, Abdenour Hadid, and Yanwei Pang. Deep Learning in Object Detection and Recognition. Springer, 2019.

K, Jurgen Ronald, and Society of Automotive Engineers, eds. Object detection, collision warning, and avoidance systems. Warrendale, PA: Society of Automotive Engineers, 1998.

Jiang, Xiaoyue, Eric Granger, Abdenour Hadid, Yanwei Pang, and Xiaoyi Feng. Deep Learning in Object Detection and Recognition. Springer, 2021.

Remote Sensing for Target Object Detection and Identification. MDPI, 2020. http://dx.doi.org/10.3390/books978-3-03928-333-0.

1949-, Kasturi Rangachar, and United States. National Aeronautics and Space Administration., eds. 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.

Yuan-Liang, Tang, Devadiga Sadashiva, and United States. National Aeronautics and Space Administration., eds. 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.

Yuan-Liang, Tang, Devadiga Sadashiva, and United States. National Aeronautics and Space Administration., eds. 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.

2D Object Detection and Recognition: Models, Algorithms, and Networks. The MIT Press, 2002.

Michelucci, Umberto. Advanced Applied Deep Learning: Convolutional Neural Networks and Object Detection. Apress, 2019.

Mangalindan, Diane Marie J. Children's detection and use of cues to infer object displacement. 2007.