Literatura académica sobre el tema "Invariant Object Recognition"
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Artículos de revistas sobre el tema "Invariant Object Recognition"
Wood, Justin N. y Samantha M. W. Wood. "The development of newborn object recognition in fast and slow visual worlds". Proceedings of the Royal Society B: Biological Sciences 283, n.º 1829 (27 de abril de 2016): 20160166. http://dx.doi.org/10.1098/rspb.2016.0166.
Texto completoIsik, Leyla, Ethan M. Meyers, Joel Z. Leibo y Tomaso Poggio. "The dynamics of invariant object recognition in the human visual system". Journal of Neurophysiology 111, n.º 1 (1 de enero de 2014): 91–102. http://dx.doi.org/10.1152/jn.00394.2013.
Texto completoDiCarlo, James J. y David D. Cox. "Untangling invariant object recognition". Trends in Cognitive Sciences 11, n.º 8 (agosto de 2007): 333–41. http://dx.doi.org/10.1016/j.tics.2007.06.010.
Texto completoStejskal, Tomáš. "2D-Shape Analysis Using Shape Invariants". Applied Mechanics and Materials 613 (agosto de 2014): 452–57. http://dx.doi.org/10.4028/www.scientific.net/amm.613.452.
Texto completoSchurgin, Mark y Jonathan Flombaum. "Invariant object recognition enhanced by object persistence". Journal of Vision 15, n.º 12 (1 de septiembre de 2015): 239. http://dx.doi.org/10.1167/15.12.239.
Texto completoCox, David D., Philip Meier, Nadja Oertelt y James J. DiCarlo. "'Breaking' position-invariant object recognition". Nature Neuroscience 8, n.º 9 (7 de agosto de 2005): 1145–47. http://dx.doi.org/10.1038/nn1519.
Texto completoRolls, Edmund T. y Simon M. Stringer. "Invariant visual object recognition: A model, with lighting invariance". Journal of Physiology-Paris 100, n.º 1-3 (julio de 2006): 43–62. http://dx.doi.org/10.1016/j.jphysparis.2006.09.004.
Texto completoCHAN, LAI-WAN. "NEURAL NETWORKS FOR COLLECTIVE TRANSLATIONAL INVARIANT OBJECT RECOGNITION". International Journal of Pattern Recognition and Artificial Intelligence 06, n.º 01 (abril de 1992): 143–56. http://dx.doi.org/10.1142/s0218001492000084.
Texto completoSufi karimi, Hiwa y Karim Mohammadi. "Rotational invariant biologically inspired object recognition". IET Image Processing 14, n.º 15 (diciembre de 2020): 3762–73. http://dx.doi.org/10.1049/iet-ipr.2019.1621.
Texto completoKim, Kye-Kyung, Jae-Hong Kim y Jae-Yun Lee. "Illumination and Rotation Invariant Object Recognition". Journal of the Korea Contents Association 12, n.º 11 (28 de noviembre de 2012): 1–8. http://dx.doi.org/10.5392/jkca.2012.12.11.001.
Texto completoTesis sobre el tema "Invariant Object Recognition"
Srestasathiern, Panu. "View Invariant Planar-Object Recognition". The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1420564069.
Texto completoTonge, Ashwini Kishor. "Object Recognition Using Scale-Invariant Chordiogram". Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984116/.
Texto completoDahmen, Jörg. "Invariant image object recognition using Gaussian mixture densities". [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=964586940.
Texto completoBooth, Michael C. A. "Temporal lobe mechanisms for view-invariant object recognition". Thesis, University of Oxford, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299094.
Texto completoHsu, Tao-i. "Affine invariant object recognition by voting match techniques". Thesis, Monterey, California. Naval Postgraduate School, 1988. http://hdl.handle.net/10945/22865.
Texto completoThis thesis begins with a general survey of different model based systems for object recognition. The advantage and disadvantage of those systems are discussed. A system is then selected for study because of its effective Affine invariant matching [Ref. 1] characteristic. This system involves two separate phases, the modeling and the recognition. One is done off-line and the other is done on-line. A Hashing technique is implemented to achieve fast accessing and voting. Different test data sets are used in experiments to illustrate the recognition capabilities of this system. This demonstrates the capabilities of partial match, recognizing objects under similarity transformation applied to the models, and the results of noise perturbation. The testing results are discussed, and related experiences and recommendations are presented.
http://archive.org/details/affineinvarianto00hsut
Captain, Taiwan Republic of China Army
Robinson, Leigh. "Invariant object recognition : biologically plausible and machine learning approaches". Thesis, University of Warwick, 2015. http://wrap.warwick.ac.uk/83167/.
Texto completoAllan, Moray. "Sprite learning and object category recognition using invariant features". Thesis, University of Edinburgh, 2007. http://hdl.handle.net/1842/2430.
Texto completoBone, Peter. "Fully invariant object recognition and tracking from cluttered scenes". Thesis, University of Sussex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.444109.
Texto completoBanarse, D. S. "A generic neural network architecture for deformation invariant object recognition". Thesis, Bangor University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362146.
Texto completoSim, Hak Chuah. "Invariant object matching with a modified dynamic link network". Thesis, University of Southampton, 1999. https://eprints.soton.ac.uk/256269/.
Texto completoLibros sobre el tema "Invariant Object Recognition"
Object recognition through invariant indexing. Oxford: Oxford University Press, 1995.
Buscar texto completoLamdan, Yehezkel. Object recognition by affine invariant matching. New York: Courant Institute of Mathematical Sciences, New York University, 1988.
Buscar texto completoGrace, Alan Edward. Adaptive segmentation for aspect invariant object recognition. Birmingham: Universityof Birmingham, 1993.
Buscar texto completoHsu, Tao-i. Affine invariant object recognition by voting match techniques. Monterey, Calif: Naval Postgraduate School, 1988.
Buscar texto completoKyrki, Ville. Local and global feature extraction for invariant object recognition. Lappeenranta, Finland: Lappeenranta University of Technology, 2002.
Buscar texto completoSoucek, Branko. Fast learning and invariant object recognition: The sixth-generation breakthrough. New York: Wiley, 1992.
Buscar texto completoGroup, IRIS, ed. Fast learning and invariant object recognition: The sixth-generation breakthrough. New York: Wiley, 1992.
Buscar texto completoLee, Raymond Shu Tak. Invariant object recognition based on elastic graph matching: Theory and applications. Amsterdam: IOS Press, 2003.
Buscar texto completoReiss, Thomas H. Recognizing planar objects using invariant image features. Berlin: Springer-Verlag, 1993.
Buscar texto completoRothwell, C. a. Object Recognition Through Invariant Indexing. Oxford University Press, 1995.
Buscar texto completoCapítulos de libros sobre el tema "Invariant Object Recognition"
Rodrigues, João y J. M. Hans du Buf. "Invariant Multi-scale Object Categorisation and Recognition". En Pattern Recognition and Image Analysis, 459–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72847-4_59.
Texto completoBart, Evgeniy, Evgeny Byvatov y Shimon Ullman. "View-Invariant Recognition Using Corresponding Object Fragments". En Lecture Notes in Computer Science, 152–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24671-8_12.
Texto completoBen-Arie, Jezekiel y Zhiqian Wang. "Gabor kernels for affine—invariant object recognition". En Gabor Analysis and Algorithms, 409–26. Boston, MA: Birkhäuser Boston, 1998. http://dx.doi.org/10.1007/978-1-4612-2016-9_14.
Texto completoVillamizar, Michael, Alberto Sanfeliu y Juan Andrade-Cetto. "Orientation Invariant Features for Multiclass Object Recognition". En Lecture Notes in Computer Science, 655–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11892755_68.
Texto completoWechsler, Harry. "Network Representations and Match Filters for Invariant Object Recognition". En Pattern Recognition Theory and Applications, 269–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83069-3_21.
Texto completoYang, Mingqiang, Kidiyo Kpalma y Joseph Ronsin. "Shape-Based Invariant Feature Extraction for Object Recognition". En Advances in Reasoning-Based Image Processing Intelligent Systems, 255–314. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24693-7_9.
Texto completoLi, Zhenxiao y Liqing Zhang. "Affine Invariant Topic Model for Generic Object Recognition". En Advances in Neural Networks - ISNN 2010, 152–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13318-3_20.
Texto completoTeo, Choon Hui y Yong Haur Tay. "Invariant Object Recognition Using Circular Pairwise Convolutional Networks". En Lecture Notes in Computer Science, 1232–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-36668-3_167.
Texto completoChen, Guangyi, Tien Dai Bui, Adam Krzyzak y Yongjia Zhao. "Invariant Object Recognition Using Radon and Fourier Transforms". En Advances in Neural Networks – ISNN 2013, 650–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39065-4_78.
Texto completoPatekar, Rahul y Abhijeet Nandedkar. "Distance Invariant RGB-D Object Recognition Using DSMS System". En Communications in Computer and Information Science, 135–48. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6315-7_11.
Texto completoActas de conferencias sobre el tema "Invariant Object Recognition"
Jouan, Alexandre y Henri H. Arsenault. "Invariant principal components for pattern recognition". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/oam.1987.ma1.
Texto completoSrestasathiern, Panu y Alper Yilmaz. "View invariant object recognition". En 2008 19th International Conference on Pattern Recognition (ICPR). IEEE, 2008. http://dx.doi.org/10.1109/icpr.2008.4761238.
Texto completoYu, Francis T. S., Xiaoyang Li, Eddy Tam y Don A. Gregory. "Joint transformation correlation implementation of the circular harmonic expansion for pattern recognition". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1988. http://dx.doi.org/10.1364/oam.1988.mv7.
Texto completoLejeune, Claude, Young Sheng y Henri H. Arsenault. "Optoneural system for invariant pattern recognition". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.mii2.
Texto completoStiller, Peter F. "Global invariant methods for object recognition". En International Symposium on Optical Science and Technology, editado por Longin J. Latecki, David M. Mount, Angela Y. Wu y Robert A. Melter. SPIE, 2001. http://dx.doi.org/10.1117/12.447278.
Texto completoSheng, Yunlong y Henri H. Arsenault. "Shift invariant Fourier-Mellin features for pattern recognition". En OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1988. http://dx.doi.org/10.1364/oam.1988.fp6.
Texto completoLi, Bingcheng. "Mask size independent and orientation invariant object finding". En Automatic Target Recognition XXVIII, editado por Firooz A. Sadjadi y Abhijit Mahalanobis. SPIE, 2018. http://dx.doi.org/10.1117/12.2305571.
Texto completoRaytchev, Bisser, Tetsuya Mino, Toru Tamaki y Kazufumi Kaneda. "View-Invariant Object Recognition with Visibility Maps". En 2010 20th International Conference on Pattern Recognition (ICPR). IEEE, 2010. http://dx.doi.org/10.1109/icpr.2010.260.
Texto completoUrolagin, Siddhaling, K. V. Prema y N. V. Subba Reddy. "Rotation invariant object recognition using Gabor filters". En 2010 5th International Conference on Industrial and Information Systems (ICIIS). IEEE, 2010. http://dx.doi.org/10.1109/iciinfs.2010.5578669.
Texto completoGanesharajah, B., S. Mahesan y U. A. J. Pinidiyaarachchi. "Robust invariant descriptors for visual object recognition". En 2011 IEEE 6th International Conference on Industrial and Information Systems (ICIIS). IEEE, 2011. http://dx.doi.org/10.1109/iciinfs.2011.6038059.
Texto completoInformes sobre el tema "Invariant Object Recognition"
Nagao, Kenji y Eric Grimson. Object Recognition by Alignment Using Invariant Projections of Planar Surfaces. Fort Belvoir, VA: Defense Technical Information Center, diciembre de 1994. http://dx.doi.org/10.21236/ada279841.
Texto completoVoils, Danny. Scale Invariant Object Recognition Using Cortical Computational Models and a Robotic Platform. Portland State University Library, enero de 2000. http://dx.doi.org/10.15760/etd.632.
Texto completoKim, Dae-Shik. Predictive Coding Strategies for Invariant Object Recognition and Volitional Motion Control in Neuromorphic Agents. Fort Belvoir, VA: Defense Technical Information Center, septiembre de 2015. http://dx.doi.org/10.21236/ada626818.
Texto completoSerre, Thomas y Maximilian Riesenhuber. Realistic Modeling of Simple and Complex Cell Tuning in the HMAX Model, and Implications for Invariant Object Recognition in Cortex. Fort Belvoir, VA: Defense Technical Information Center, julio de 2004. http://dx.doi.org/10.21236/ada459692.
Texto completoWeiss, Isaac. Geometric Invariants and Object Recognition. Fort Belvoir, VA: Defense Technical Information Center, agosto de 1992. http://dx.doi.org/10.21236/ada255317.
Texto completoLogothetis, Nikos K., Thomas Vetter, Anya Hurlbert y Tomaso Poggio. View-Based Models of 3D Object Recognition and Class-Specific Invariance. Fort Belvoir, VA: Defense Technical Information Center, abril de 1994. http://dx.doi.org/10.21236/ada279858.
Texto completoKokurina, O. Yu. VIABILITY AND RESILIENCE OF THE MODERN STATE: PATTERNS OF PUBLIC-LEGAL ADMINISTRATION AND REGULATION. Kokurina O.Yu., febrero de 2022. http://dx.doi.org/10.12731/kokurina-21-011-31155.
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