Informative Feature Selection for Object Recognition via Sparse PCA∗ Nikhil Naikal, Allen Y. Yang, and S. Shankar Sastry Department of EECS, University of California, Berkeley {nnaikal, yang, sastry - Sparse PCA - Document - PDFSEARCH.IO

First Page		Document Content
Date: 2011-06-10 12:51:40 Mathematics Singular value decomposition Data analysis Computer vision Principal component analysis Eigenvalues and eigenvectors Object recognition Bundle adjustment Matrix Statistics Algebra Multivariate statistics		Informative Feature Selection for Object Recognition via Sparse PCA∗ Nikhil Naikal, Allen Y. Yang, and S. Shankar Sastry Department of EECS, University of California, Berkeley {nnaikal, yang, sastry}@eecs.berkeley.edu Add to Reading List Source URL: www.eecs.berkeley.edu Download Document from Source Website File Size: 1,72 MB Share Document on Facebook

	Task Learning through Visual Demonstration and Situated Dialogue Changsong Liu and Joyce Y. Chai Nishant Shukla and Song-Chun Zhu Department of Computer Science and Engineering Center for Vision, Cognition, Learning and DocID: 1xUvD - View Document
	Paper accepted at the European Conf. on Computer Vision (ECCV), Munich, Semi-Dense 3D Reconstruction with a Stereo Event Camera Yi Zhou1,2 , Guillermo Gallego3 , Henri Rebecq3 , Laurent Kneip4 , Hongdong Li1,2 , a DocID: 1xU8u - View Document
	Computer Vision Winter Workshop 2008, Janez Perˇs (ed.) Moravske Toplice, Slovenia, February 4–6 Slovenian Pattern Recognition Society, Ljubljana, Slovenia A Lower Bound by One-against-all Decomposition for Potts Mode DocID: 1vs97 - View Document
	Internationl Journal of Computer Vision manuscript No. (will be inserted by the editor) Augmented Reality Meets Computer Vision Efficient Data Generation for Urban Driving Scenes Hassan Abu Alhaija1,2 · Siva Karthik Mus DocID: 1vpMo - View Document
	Siamese Network： Architecture and Applications in Computer Vision Tech Report Dec 30, 2014 Hengliang Luo DocID: 1vp5V - View Document