Object detection

Results: 550



#Item
471Salient Object Detection for Searched Web Images via Global Saliency Peng Wang1 Jingdong Wang2 Gang Zeng1 Jie Feng1 Hongbin Zha1 Shipeng Li2 1 Key Laboratory on Machine Perception, Peking University 2 Microsoft Research

Salient Object Detection for Searched Web Images via Global Saliency Peng Wang1 Jingdong Wang2 Gang Zeng1 Jie Feng1 Hongbin Zha1 Shipeng Li2 1 Key Laboratory on Machine Perception, Peking University 2 Microsoft Research

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Source URL: research.microsoft.com

Language: English - Date: 2012-03-30 05:59:33
472Rich feature hierarchies for accurate object detection and semantic segmentation Tech report Ross Girshick1 Jeff Donahue1,2 Trevor Darrell1,2 1

Rich feature hierarchies for accurate object detection and semantic segmentation Tech report Ross Girshick1 Jeff Donahue1,2 Trevor Darrell1,2 1

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Source URL: arxiv.org

Language: English - Date: 2013-11-11 20:26:01
473Distinctive Image Features from Scale-Invariant Keypoints David G. Lowe Computer Science Department University of British Columbia Vancouver, B.C., Canada

Distinctive Image Features from Scale-Invariant Keypoints David G. Lowe Computer Science Department University of British Columbia Vancouver, B.C., Canada

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Source URL: www.cs.ubc.ca

Language: English - Date: 2012-01-23 21:31:46
47498  IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 29,

98 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 29,

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Source URL: www.cs.umd.edu

Language: English - Date: 2007-06-27 14:26:52
475Computer Vision Kitware’s Computer Vision team is a leader in the creation and support of state-of-the-art technology, providing robust solutions to academic and government institutions, such as DARPA, IARPA, and the A

Computer Vision Kitware’s Computer Vision team is a leader in the creation and support of state-of-the-art technology, providing robust solutions to academic and government institutions, such as DARPA, IARPA, and the A

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Source URL: www.kitware.com

Language: English - Date: 2012-10-08 13:36:56
476Invited Applications Paper  Discriminative Latent Variable Models for Object Detection Pedro Felzenszwalb University of Chicago

Invited Applications Paper Discriminative Latent Variable Models for Object Detection Pedro Felzenszwalb University of Chicago

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Source URL: www.icml2010.org

Language: English - Date: 2010-06-13 09:06:58
477Online Feature Selection for Pixel Classification Karen Glocer [removed] Department of Computer Science, University of California Santa Cruz, Santa Cruz, CA[removed]USA Damian Eads James Theiler

Online Feature Selection for Pixel Classification Karen Glocer [removed] Department of Computer Science, University of California Santa Cruz, Santa Cruz, CA[removed]USA Damian Eads James Theiler

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Source URL: www.machinelearning.org

Language: English - Date: 2008-12-01 11:14:32
478arXiv:1110.6181v1 [astro-ph.EP] 27 Oct[removed]Detection Technique for Artificially-Illuminated Objects in the Outer Solar System and Beyond Abraham Loeb1,2 and Edwin L. Turner3,4 1

arXiv:1110.6181v1 [astro-ph.EP] 27 Oct[removed]Detection Technique for Artificially-Illuminated Objects in the Outer Solar System and Beyond Abraham Loeb1,2 and Edwin L. Turner3,4 1

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Source URL: arxiv.org

Language: English - Date: 2013-09-25 00:36:11
479TOP-10 MYTHS OF LIGHTNING SAFETY 1. MYTH: Lightning Never Strikes The Same Place Twice TRUTH: Lightning often strikes the same place repeatedly, especially if it’s a tall isolated pointy object. The Empire State Buildi

TOP-10 MYTHS OF LIGHTNING SAFETY 1. MYTH: Lightning Never Strikes The Same Place Twice TRUTH: Lightning often strikes the same place repeatedly, especially if it’s a tall isolated pointy object. The Empire State Buildi

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Source URL: www.struckbylightning.org

Language: English - Date: 2010-03-07 15:26:27
480[removed]Hardware Evaluation of Heavy Truck Side and Rear Object Detection Systems W. Riley Garrott and Mark A. Flick National Highway Traffic Safety Administration

[removed]Hardware Evaluation of Heavy Truck Side and Rear Object Detection Systems W. Riley Garrott and Mark A. Flick National Highway Traffic Safety Administration

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Source URL: www.nhtsa.gov

Language: English - Date: 2010-03-17 21:17:22