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Artykuły w czasopismach na temat "Object invariants"
Samad, Saleha, Anam Haq i Shoab A. Khan. "Orientation Invariant Object Recognitions Using Geometric Moments Invariants and Color Histograms". International Journal of Computer and Electrical Engineering 7, nr 2 (2015): 101–8. http://dx.doi.org/10.17706/ijcee.2015.v7.876.
Pełny tekst źródłaNGUYEN, THU-TRANG, NINH-THUAN TRUONG i VIET-HA NGUYEN. "VERIFYING JAVA OBJECT INVARIANTS AT RUNTIME". International Journal of Software Engineering and Knowledge Engineering 21, nr 04 (czerwiec 2011): 605–19. http://dx.doi.org/10.1142/s0218194011005281.
Pełny tekst źródłaStejskal, Tomáš. "2D-Shape Analysis Using Shape Invariants". Applied Mechanics and Materials 613 (sierpień 2014): 452–57. http://dx.doi.org/10.4028/www.scientific.net/amm.613.452.
Pełny tekst źródłaChang, Bor-Yuh Evan, K. Rustan i M. Leino. "Inferring Object Invariants". Electronic Notes in Theoretical Computer Science 131 (maj 2005): 63–74. http://dx.doi.org/10.1016/j.entcs.2005.01.023.
Pełny tekst źródłaPagano, Christopher C., i Michael T. Turvey. "Eigenvectors of the Inertia Tensor and Perceiving the Orientations of Limbs and Objects". Journal of Applied Biomechanics 14, nr 4 (listopad 1998): 331–59. http://dx.doi.org/10.1123/jab.14.4.331.
Pełny tekst źródłaLASENBY, JOAN, i EDUARDO BAYRO-CORROCHANO. "ANALYSIS AND COMPUTATION OF PROJECTIVE INVARIANTS FROM MULTIPLE VIEWS IN THE GEOMETRIC ALGEBRA FRAMEWORKS". International Journal of Pattern Recognition and Artificial Intelligence 13, nr 08 (grudzień 1999): 1105–21. http://dx.doi.org/10.1142/s0218001499000628.
Pełny tekst źródłaRivlin, Ehud, i Isaac Weiss. "Deformation Invariants in Object Recognition". Computer Vision and Image Understanding 65, nr 1 (styczeń 1997): 95–108. http://dx.doi.org/10.1006/cviu.1996.0478.
Pełny tekst źródłaWeiss, Isaac. "Geometric invariants and object recognition". International Journal of Computer Vision 10, nr 3 (czerwiec 1993): 207–31. http://dx.doi.org/10.1007/bf01539536.
Pełny tekst źródłaLu, Wei. "Image Retrieval Based on Contour and Relevance Feedback". Applied Mechanics and Materials 182-183 (czerwiec 2012): 1771–75. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1771.
Pełny tekst źródłaShan, J. "Photogrammetric object description with projective invariants". ISPRS Journal of Photogrammetry and Remote Sensing 52, nr 5 (październik 1997): 222–28. http://dx.doi.org/10.1016/s0924-2716(97)00015-4.
Pełny tekst źródłaRozprawy doktorskie na temat "Object invariants"
Self, T. Benjamin (Thomas Benjamin) 1977. "Expression and localization of object invariants". Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86498.
Pełny tekst źródłaIncludes bibliographical references (leaf 23).
by T. Benjamin Self.
S.B.and M.Eng.
Vinther, Sven. "Active 3D object recognition using geometric invariants". Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362974.
Pełny tekst źródłaBeis, Jeffrey S. "Indexing without invariants in model-based object recognition". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq25014.pdf.
Pełny tekst źródłaZhu, Yonggen. "Feature extraction and 2D/3D object recognition using geometric invariants". Thesis, King's College London (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362731.
Pełny tekst źródłaSoysal, Medeni. "Joint Utilization Of Local Appearance Descriptors And Semi-local Geometry For Multi-view Object Recognition". Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614313/index.pdf.
Pełny tekst źródłas local feature frameworks and previous decade&rsquo
s strong but deserted geometric invariance field are presented in this dissertation. The rationale behind this effort is to complement the lowered discriminative capacity of local features, by the invariant geometric descriptions. Similar to our predecessors, we first start with constrained cases and then extend the applicability of our methods to more general scenarios. Local features approach, on which our methods are established, is reviewed in three parts
namely, detectors, descriptors and the methods of object recognition that employ them. Next, a novel planar object recognition framework that lifts the requirement for exact appearance-based local feature matching is presented. This method enables matching of groups of features by utilizing both appearance information and group geometric descriptions. An under investigated area, scene logo recognition, is selected for real life application of this method. Finally, we present a novel method for three-dimensional (3D) object recognition, which utilizes well-known local features in a more efficient way without any reliance on partial or global planarity. Geometrically consistent local features, which form the crucial basis for object recognition, are identified using affine 3D geometric invariants. The utilization of 3D geometric invariants replaces the classical 2D affine transform estimation /verification step, and provides the ability to directly verify 3D geometric consistency. The accuracy and robustness of the proposed method in highly cluttered scenes with no prior segmentation or post 3D reconstruction requirements, are presented during the experiments.
Wilhelm, Hedwig. "A Neural Network Model of Invariant Object Identification". Doctoral thesis, Universitätsbibliothek Leipzig, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-62050.
Pełny tekst źródłaSrestasathiern, Panu. "View Invariant Planar-Object Recognition". The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1420564069.
Pełny tekst źródłaTonge, Ashwini Kishor. "Object Recognition Using Scale-Invariant Chordiogram". Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984116/.
Pełny tekst źródłaDahmen, Jörg. "Invariant image object recognition using Gaussian mixture densities". [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=964586940.
Pełny tekst źródłaBooth, 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.
Pełny tekst źródłaKsiążki na temat "Object invariants"
Object recognition through invariant indexing. Oxford: Oxford University Press, 1995.
Znajdź pełny tekst źródłaLamdan, Yehezkel. Object recognition by affine invariant matching. New York: Courant Institute of Mathematical Sciences, New York University, 1988.
Znajdź pełny tekst źródłaGrace, Alan Edward. Adaptive segmentation for aspect invariant object recognition. Birmingham: Universityof Birmingham, 1993.
Znajdź pełny tekst źródłaKao, Chang-Lung. Affine invariant matching of noisy objects. Monterey, Calif: Naval Postgraduate School, 1989.
Znajdź pełny tekst źródłaHsu, Tao-i. Affine invariant object recognition by voting match techniques. Monterey, Calif: Naval Postgraduate School, 1988.
Znajdź pełny tekst źródłaReiss, Thomas H. Recognizing planar objects using invariant image features. Berlin: Springer-Verlag, 1993.
Znajdź pełny tekst źródłaReiss, Thomas H., red. Recognizing Planar Objects Using Invariant Image Features. Berlin/Heidelberg: Springer-Verlag, 1993. http://dx.doi.org/10.1007/bfb0017553.
Pełny tekst źródłaKyrki, Ville. Local and global feature extraction for invariant object recognition. Lappeenranta, Finland: Lappeenranta University of Technology, 2002.
Znajdź pełny tekst źródłaGroup, IRIS, red. Fast learning and invariant object recognition: The sixth-generation breakthrough. New York: Wiley, 1992.
Znajdź pełny tekst źródłaSoucek, Branko. Fast learning and invariant object recognition: The sixth-generation breakthrough. New York: Wiley, 1992.
Znajdź pełny tekst źródłaCzęści książek na temat "Object invariants"
Leino, K. Rustan M., i Peter Müller. "Object Invariants in Dynamic Contexts". W ECOOP 2004 – Object-Oriented Programming, 491–515. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24851-4_22.
Pełny tekst źródłaRothwell, Charles A. "Hierarchical object description using invariants". W Applications of Invariance in Computer Vision, 397–414. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58240-1_21.
Pełny tekst źródłaJackson, Daniel. "Object models as heap invariants". W Monographs in Computer Science, 247–68. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21798-7_12.
Pełny tekst źródłaMuselet, Damien, i Brian Funt. "Color Invariants for Object Recognition". W Advanced Color Image Processing and Analysis, 327–76. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-6190-7_10.
Pełny tekst źródłaBalzer, Stephanie, i Thomas R. Gross. "Verifying Multi-object Invariants with Relationships". W Lecture Notes in Computer Science, 358–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22655-7_17.
Pełny tekst źródłaNair, Sreeja S., Gustavo Petri i Marc Shapiro. "Proving the Safety of Highly-Available Distributed Objects". W Programming Languages and Systems, 544–71. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44914-8_20.
Pełny tekst źródłaGopinathan, Madhu, i Sriram K. Rajamani. "Runtime Monitoring of Object Invariants with Guarantee". W Runtime Verification, 158–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-89247-2_10.
Pełny tekst źródłaNaumann, David A. "Assertion-Based Encapsulation, Object Invariants and Simulations". W Formal Methods for Components and Objects, 251–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11561163_11.
Pełny tekst źródłaHuizing, Kees, i Ruurd Kuiper. "Verification of Object Oriented Programs Using Class Invariants". W Fundamental Approaches to Software Engineering, 208–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-46428-x_15.
Pełny tekst źródłaLau, K. L., W. C. Siu i N. F. Law. "Improved Scheme for Object Searching Using Moment Invariants". W Advances in Multimedia Information Processing — PCM 2002, 783–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36228-2_97.
Pełny tekst źródłaStreszczenia konferencji na temat "Object invariants"
Leino, K. Rustan M., i Angela Wallenburg. "Class-local object invariants". W the 1st conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1342211.1342225.
Pełny tekst źródłaKautsky, Jaroslav, Jan Flusser i Filip Sroubek. "Implicit Invariants and Object Recognition". W 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications (DICTA 2007). IEEE, 2007. http://dx.doi.org/10.1109/dicta.2007.4426833.
Pełny tekst źródłaFahndrich, Manuel, i Songtao Xia. "Establishing object invariants with delayed types". W the 22nd annual ACM SIGPLAN conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1297027.1297052.
Pełny tekst źródłaSummers, Alexander J., Sophia Drossopoulou i Peter Müller. "The need for flexible object invariants". W International Workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1562154.1562160.
Pełny tekst źródłaXiao, Bai, Richard Wilson i Edwin Hancock. "Object recognition using graph spectral invariants". W 2008 19th International Conference on Pattern Recognition (ICPR). IEEE, 2008. http://dx.doi.org/10.1109/icpr.2008.4761245.
Pełny tekst źródłaGong, Weibo. "Invariants in Object Deformation and Concept Abstraction". W 2018 IEEE Conference on Decision and Control (CDC). IEEE, 2018. http://dx.doi.org/10.1109/cdc.2018.8619352.
Pełny tekst źródłaTham, Jie Sheng, Yong-Shen Chen, Mohammad Faizal Ahmad Fauzi i Yoong Choon Chang. "Depth image object recognition using moment invariants". W 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW). IEEE, 2016. http://dx.doi.org/10.1109/icce-tw.2016.7520900.
Pełny tekst źródłaRahtu, E., M. Salo, J. Heikkil i J. Flusser. "Generalized affine moment invariants for object recogn". W 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.599.
Pełny tekst źródłaJannson, Tomasz P. "Manifold geometric invariants and object-centric approach". W International Symposium on Optical Science and Technology, redaktorzy Bruno Bosacchi, David B. Fogel i James C. Bezdek. SPIE, 2002. http://dx.doi.org/10.1117/12.453564.
Pełny tekst źródłaBayro-Corrochano, E., i C. Lopez-Franco. "Invariants and omnidirectional vision for robot object recognition". W 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2005. http://dx.doi.org/10.1109/iros.2005.1545165.
Pełny tekst źródłaRaporty organizacyjne na temat "Object invariants"
Weiss, Isaac. Geometric Invariants and Object Recognition. Fort Belvoir, VA: Defense Technical Information Center, sierpień 1992. http://dx.doi.org/10.21236/ada255317.
Pełny tekst źródłaWeiss, Isaac, i Manjit Ray. Recognizing Articulated Objects in Range Images Using Invariants. Fort Belvoir, VA: Defense Technical Information Center, luty 2002. http://dx.doi.org/10.21236/ada408100.
Pełny tekst źródłaKeren, David, Ehud Rivlin, Han Shimshoni i Isaac Weiss. Recognizing 3D Objects Using Tactile Sensing and Curve Invariants. Fort Belvoir, VA: Defense Technical Information Center, lipiec 1997. http://dx.doi.org/10.21236/ada353693.
Pełny tekst źródłaNagao, Kenji, i Eric Grimson. Object Recognition by Alignment Using Invariant Projections of Planar Surfaces. Fort Belvoir, VA: Defense Technical Information Center, grudzień 1994. http://dx.doi.org/10.21236/ada279841.
Pełny tekst źródłaVoils, Danny. Scale Invariant Object Recognition Using Cortical Computational Models and a Robotic Platform. Portland State University Library, styczeń 2000. http://dx.doi.org/10.15760/etd.632.
Pełny tekst źródłaLogothetis, Nikos K., Thomas Vetter, Anya Hurlbert i Tomaso Poggio. View-Based Models of 3D Object Recognition and Class-Specific Invariance. Fort Belvoir, VA: Defense Technical Information Center, kwiecień 1994. http://dx.doi.org/10.21236/ada279858.
Pełny tekst źródłaKim, Dae-Shik. Predictive Coding Strategies for Invariant Object Recognition and Volitional Motion Control in Neuromorphic Agents. Fort Belvoir, VA: Defense Technical Information Center, wrzesień 2015. http://dx.doi.org/10.21236/ada626818.
Pełny tekst źródłaSerre, Thomas, i 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, lipiec 2004. http://dx.doi.org/10.21236/ada459692.
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