Part-based models

Results: 51



#Item
21Web-based Models for Natural Language Processing MIRELLA LAPATA and FRANK KELLER University of Edinburgh Previous work demonstrated that web counts can be used to approximate bigram counts, thus suggesting that web-based

Web-based Models for Natural Language Processing MIRELLA LAPATA and FRANK KELLER University of Edinburgh Previous work demonstrated that web counts can be used to approximate bigram counts, thus suggesting that web-based

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Source URL: homepages.inf.ed.ac.uk

Language: English - Date: 2006-01-25 12:04:52
22Position Statement on  Physician Assistants Team-based models of medical care that are characterised by responsiveness to local needs, mutual reliance and flexibility have always been a part of rural and remote medicine.

Position Statement on Physician Assistants Team-based models of medical care that are characterised by responsiveness to local needs, mutual reliance and flexibility have always been a part of rural and remote medicine.

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Source URL: www.acrrm.org.au

Language: English - Date: 2014-04-03 14:48:42
23Spatial Priors for Part-Based Recognition using Statistical Models David Crandall1 Cornell University [removed]  Pedro Felzenszwalb

Spatial Priors for Part-Based Recognition using Statistical Models David Crandall1 Cornell University [removed] Pedro Felzenszwalb

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Source URL: vision.soic.indiana.edu

Language: English - Date: 2014-08-03 00:38:07
24Pictorial Structures for Object Recognition Pedro F. Felzenszwalb Artificial Intelligence Lab, Massachusetts Institute of Technology [removed] Daniel P. Huttenlocher Computer Science Department, Cornell University

Pictorial Structures for Object Recognition Pedro F. Felzenszwalb Artificial Intelligence Lab, Massachusetts Institute of Technology [removed] Daniel P. Huttenlocher Computer Science Department, Cornell University

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Source URL: www.cs.cornell.edu

Language: English - Date: 2004-04-04 22:57:52
25Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition David J. Crandall and Daniel P. Huttenlocher Cornell University, Ithaca, NY 14850, USA, {crandall,dph}@cs.cornell.edu

Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition David J. Crandall and Daniel P. Huttenlocher Cornell University, Ithaca, NY 14850, USA, {crandall,dph}@cs.cornell.edu

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Source URL: vision.soic.indiana.edu

Language: English - Date: 2014-08-03 00:38:09
26Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition David J. Crandall and Daniel P. Huttenlocher Cornell University, Ithaca, NY 14850, USA, {crandall,dph}@cs.cornell.edu

Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition David J. Crandall and Daniel P. Huttenlocher Cornell University, Ithaca, NY 14850, USA, {crandall,dph}@cs.cornell.edu

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Source URL: www.cs.cornell.edu

Language: English - Date: 2006-02-18 10:40:24
27Spatial Priors for Part-Based Recognition using Statistical Models David Crandall1 Cornell University [removed]  Pedro Felzenszwalb

Spatial Priors for Part-Based Recognition using Statistical Models David Crandall1 Cornell University [removed] Pedro Felzenszwalb

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Source URL: www.cs.cornell.edu

Language: English - Date: 2005-04-11 14:45:39
281  Object Detection with Discriminatively Trained Part Based Models Pedro F. Felzenszwalb, Ross B. Girshick, David McAllester and Deva Ramanan Abstract—We describe an object detection system based on mixtures of multis

1 Object Detection with Discriminatively Trained Part Based Models Pedro F. Felzenszwalb, Ross B. Girshick, David McAllester and Deva Ramanan Abstract—We describe an object detection system based on mixtures of multis

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Source URL: www.cs.berkeley.edu

Language: English - Date: 2013-05-01 18:04:34
29Practical 3-D Object Detection Using Category and Instance-level Appearance Models Kate Saenko, Sergey Karayev, Yangqing Jia, Alex Shyr, Allison Janoch, Jonathan Long, Mario Fritz, Trevor Darrell Abstract— Effective ro

Practical 3-D Object Detection Using Category and Instance-level Appearance Models Kate Saenko, Sergey Karayev, Yangqing Jia, Alex Shyr, Allison Janoch, Jonathan Long, Mario Fritz, Trevor Darrell Abstract— Effective ro

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Source URL: sergeykarayev.com

Language: English - Date: 2015-01-07 04:16:21
30Object Detection with Heuristic Coarse-to-Fine Search  Ross Girshick May 29, 2009  Abstract

Object Detection with Heuristic Coarse-to-Fine Search Ross Girshick May 29, 2009 Abstract

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Source URL: www.cs.berkeley.edu

Language: English - Date: 2013-05-01 18:04:37