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Object recognition
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#	Item
491	CS 294-2, Visual Grouping and Object Recognition(Prof. Jitendra Malik) August 23, 1999 Lecture #1 (The 3 Problems: Grouping, Figure/Ground and Recognition, and their Interrelationship) DRAFT Notes by Ye Sheng Add to Reading List Source URL: www.eecs.berkeley.edu Language: English - Date: 2003-07-25 14:49:12 Symmetry Object recognition Group Recall Vision Optics Mind Mental processes Computer vision
492	arXiv:1407.1610v2 [cs.CV] 22 Sep[removed]Analyzing the Performance of Multilayer Neural Networks for Object Recognition 1 Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2014-09-24 16:13:40 Electromagnetism Electronic circuits Signal processing Electronic filter Filter Electronics Electronic engineering Filter theory
493	Multiscale Combinatorial Grouping Pablo Arbel´aez1,⇤ Jordi Pont-Tuset2,⇤ 1 Jonathan T. Barron1 Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2014-04-15 22:19:21 Vision Optics Segmentation Watershed Scale space Image segment Connected-component labeling Object recognition Hierarchy Image processing Computer vision Imaging
494	Author manuscript, published in: Proceedings of ACM International Conference on Multimedia Retrieval 2011, ACM, 2011. DOI: [removed][removed]Multimedia Computing and Computer Vision Lab, Augsburg University, http:/ Add to Reading List Source URL: www.multimedia-computing.de Language: English - Date: 2013-09-10 09:38:33 Imaging Geometric hashing Video copy detection Triangle Information retrieval Feature Object recognition Recall Encoding Computer vision Vision Artificial intelligence
495	Constrained Parametric Min-Cuts for Automatic Object Segmentation Joao Carreira and Cristian Sminchisescu Computer Vision and Machine Learning Group, Institute for Numerical Simulation, Faculty of Mathematics and Natural Add to Reading List Source URL: www.eecs.berkeley.edu Language: English - Date: 2014-06-04 23:24:21 Segmentation Artificial intelligence Market segmentation GrabCut Memory segmentation Object recognition Image segment Segmentation-based object categorization Graph cuts in computer vision Image processing Computer vision Vision
496	A Category-Level 3-D Object Dataset: Putting the Kinect to Work Allison Janoch, Sergey Karayev, Yangqing Jia, Jonathan T. Barron, Mario Fritz, Kate Saenko, Trevor Darrell UC Berkeley and Max-Plank-Institute for Informati Add to Reading List Source URL: www.eecs.berkeley.edu Language: English - Date: 2013-10-18 17:47:21 Imaging Histogram of oriented gradients Kinect Object recognition Caltech 101 Computer vision Artificial intelligence Vision
497	IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 6, NO. 1, JANUARY[removed]Automatic Target Recognition by Matching Oriented Edge Pixels Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2004-02-15 19:41:35 Computer graphics Vision Pixel Edge detection Histogram equalization Image noise Object recognition Scale-invariant feature transform Image processing Computer vision Imaging
498	¨ t Augsburg Universita KAB 0 H Add to Reading List Source URL: www.multimedia-computing.de Language: English - Date: 2011-06-17 18:05:43 Statistics Feature Object recognition Probabilistic latent semantic analysis Scale space Edge detection SURF Segmentation Scale-invariant feature transform Computer vision Image processing Artificial intelligence
499	Semantic Segmentation using Regions and Parts Pablo Arbel´aez1 , Bharath Hariharan1 , Chunhui Gu1,2 , Saurabh Gupta1 , Lubomir Bourdev1,3,† and Jitendra Malik1 1 University of California, Berkeley - Berkeley, CA 94720 Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2012-04-06 12:41:08 Vision Optics Segmentation Object recognition Range segmentation One-shot learning Image processing Computer vision Imaging
500	Efficient Regression of General-Activity Human Poses from Depth Images Ross Girshick†? Jamie Shotton† Pushmeet Kohli† † Add to Reading List Source URL: www.cs.berkeley.edu Language: English - Date: 2013-05-01 18:04:34 Computational statistics Random forest Regression analysis Tree Decision tree learning Object recognition Segmentation Decision trees Artificial intelligence Statistics

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