Caltech 101

Results: 132



#Item
51Fabless semiconductor companies / GPGPU / Video cards / Graphics processing unit / Virtual reality / Parallel computing / Nvidia / ATI Technologies / GeForce / Computer hardware / Graphics hardware / Computing

Caltech Department of Computer Science CS 101.3

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Source URL: multires.caltech.edu

Language: English - Date: 2002-12-10 20:47:17
52Imaging / Histogram of oriented gradients / Kinect / Object recognition / Caltech 101 / Computer vision / Artificial intelligence / Vision

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

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Source URL: www.eecs.berkeley.edu

Language: English - Date: 2013-10-18 17:47:21
53Imaging / Computer vision / Segmentation / Caltech 101 / Figure–ground / Kadir–Brady saliency detector / Bag of words model in computer vision / Image processing / Vision / Optics

Figure - Ground Image Segmentation Helps Weakly-Supervised Learning of Objects Katerina Fragkiadaki Problem Input: An image collection containing a common object

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Source URL: www.cs.berkeley.edu

Language: English - Date: 2013-12-11 22:58:24
54Imaging / Histogram of oriented gradients / Kinect / Object recognition / Caltech 101 / Computer vision / Artificial intelligence / Vision

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

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Source URL: sergeykarayev.com

Language: English - Date: 2015-01-07 04:16:21
55Knowledge representation / Statistical natural language processing / California Institute of Technology / Caltech 101 / Probabilistic latent semantic analysis / Vocabulary / Cluster analysis / Tag / Information retrieval / Statistics / Artificial intelligence / Information science

¨ t Augsburg Universita Towards Universal Visual Vocabularies C. Ries, S. Romberg, R. Lienhart Report[removed]

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Source URL: www.multimedia-computing.de

Language: English - Date: 2011-06-17 18:05:34
56Artificial intelligence / Support vector machine / Machine learning / Bias / Data mining / California Institute of Technology / Caltech 101 / Statistics

Undoing the Damage of Dataset Bias Aditya Khosla1 , Tinghui Zhou2 , Tomasz Malisiewicz1 , Alexei A. Efros2 , and Antonio Torralba1 1 Massachusetts Institute of Technology

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Source URL: www.eecs.berkeley.edu

Language: English - Date: 2012-11-17 20:18:32
57Network architecture / Networks / Neural network / Geographic information system / Object recognition / Artificial intelligence / Science / Statistics / Caltech 101 / Computer vision / Computational neuroscience / Econometrics

PANDA: Pose Aligned Networks for Deep Attribute Modeling Ning Zhang1,2 , Manohar Paluri1 , Marc’Aurelio Ranzato1 , Trevor Darrell2 , Lubomir Bourdev1 1 2 Facebook AI Research EECS, UC Berkeley

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Source URL: www.cs.berkeley.edu

Language: English - Date: 2014-11-25 23:02:40
58Imaging / Histogram of oriented gradients / Kinect / Object recognition / Caltech 101 / Computer vision / Artificial intelligence / Vision

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

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Source URL: www.cs.berkeley.edu

Language: English - Date: 2012-07-28 19:03:14
59Computer vision / One-shot learning / Attribute / Object recognition / LabelMe / Caltech 101 / Vision / Imaging / Artificial intelligence

Understanding Objects in Detail with Fine-grained Attributes Andrea Vedaldi1 Siddharth Mahendran2 Ross Girshick5 Juho Kannala6 3

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Source URL: www.cs.berkeley.edu

Language: English - Date: 2014-04-28 08:27:30
60Network architecture / Networks / Neural network / Geographic information system / Object recognition / Artificial intelligence / Science / Statistics / Caltech 101 / Computer vision / Computational neuroscience / Econometrics

PANDA: Pose Aligned Networks for Deep Attribute Modeling Ning Zhang1,2 , Manohar Paluri1 , Marc’Aurelio Ranzato1 , Trevor Darrell2 , Lubomir Bourdev1 1 2 Facebook AI Research EECS, UC Berkeley

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Source URL: arxiv.org

Language: English - Date: 2014-05-06 21:22:49
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