Caltech 101

Results: 132



#Item
21Artificial intelligence / Symmetry / Color histogram / Bootstrapping / Caltech 101 / Shape context / Computer vision / Statistics / Vision

Annotating Historical Archives of Images Xiaoyue Wang Lexiang Ye Eamonn Keogh

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Source URL: www.cs.ucr.edu

Language: English - Date: 2008-03-20 17:40:14
22Los Angeles County /  California / Greater Los Angeles Area / Southern California / California Institute of Technology / Caltech 101 / David Forsyth

Microsoft PowerPoint - datasets_intro.ppt

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Source URL: www.frontiersincomputervision.com

Language: English - Date: 2011-09-12 00:33:29
23Imaging / Optics / Segmentation / Shape context / K-means clustering / HSL and HSV / Caltech 101 / Computer vision / Image processing / Vision

Searching the World’s Herbaria: A System for Visual Identification of Plant Species Peter N. Belhumeur1 , Daozheng Chen2 , Steven Feiner1 , David W. Jacobs2 , W. John Kress3 , Haibin Ling4 , Ida Lopez3 , Ravi Ramamoort

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Source URL: www.dabi.temple.edu

Language: English - Date: 2008-07-26 01:57:46
24Imaging / Image processing / California Institute of Technology / Caltech 101 / Search algorithms / Object recognition / K-nearest neighbor algorithm / Template matching / Visual descriptors / Computer vision / Vision / Artificial intelligence

Proximity Distribution Kernels for Geometric Context in Category Recognition Haibin Ling∗ Integrated Data Systems Department Siemens Corporate Research, Princeton, NJ haibin.ling @ siemens.com

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Source URL: www.dabi.temple.edu

Language: English - Date: 2007-08-16 15:02:16
25Imaging / Optics / Segmentation / Shape context / K-means clustering / HSL and HSV / Caltech 101 / Computer vision / Image processing / Vision

Searching the World’s Herbaria: A System for Visual Identification of Plant Species Peter N. Belhumeur1 , Daozheng Chen2 , Steven Feiner1 , David W. Jacobs2, W. John Kress3 , Haibin Ling4 , Ida Lopez3 , Ravi Ramamoorth

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Source URL: www1.cs.columbia.edu

Language: English - Date: 2009-02-02 09:13:22
26Computational statistics / Neural network / Pattern recognition / Supervised learning / Unsupervised learning / Caltech 101 / Machine learning / Artificial intelligence / Learning

Building High-level Features Using Large Scale Unsupervised Learning

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Source URL: cs.stanford.edu

Language: English - Date: 2012-07-12 00:33:34
27Digital media / Caltech 101 / Neural networks / CNN / News media / Broadcasting

Supplementary Materials Learning Deep Features for Scene Recognition using Places Database Bolei Zhou1 , Agata Lapedriza1,3 , Jianxiong Xiao2 , Antonio Torralba1 , and Aude Oliva1 1

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Source URL: places.csail.mit.edu

Language: English - Date: 2014-10-14 22:56:49
28California Institute of Technology / Caltech 101 / Image processing / Segmentation / Object detection / Object recognition / Stereopsis / Object / Category / Computer vision / Imaging / Optics

Microsoft COCO: Common Objects in Context Tsung-Yi Lin1 , Michael Maire2 , Serge Belongie1 , James Hays3 , Pietro Perona2 , Deva Ramanan4 , Piotr Doll´ ar5 , C. Lawrence Zitnick5 1

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Source URL: vision.ucsd.edu

Language: English - Date: 2014-07-06 18:50:42
29Science / Electronic engineering / Caltech 101 / Knowledge / European Conference on Computer Vision / International Conference on Computer Vision / Conference on Computer Vision and Pattern Recognition

UpdatedJIA DENG http://web.eecs.umich.edu/~jiadengHayward St, Ann Arbor, MI 48109

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Source URL: web.eecs.umich.edu

Language: English - Date: 2015-05-16 13:46:01
30Caltech 101 / LabelMe / Object recognition / Part-based models / Segmentation / Object detection / Kadir–Brady saliency detector / Boosting methods for object categorization / Computer vision / Image processing / California Institute of Technology

Detecting avocados to zucchinis: what have we done, and where are we going? Olga Russakovsky1 , Jia Deng1 , Zhiheng Huang1 , Alexander C. Berg2 , Li Fei-Fei1 Stanford University1 , UNC Chapel Hill2 Abstract

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Source URL: web.eecs.umich.edu

Language: English - Date: 2013-10-08 13:17:10
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