Caltech 101

Results: 132



#Item
111California Institute of Technology / San Gabriel Valley / Honor code / Yi / Knowledge / Education / Codes of conduct / Association of American Universities / Association of Independent Technological Universities

Minutes
for
BoD
Meeting,
August
3rd,
2011
–
Schlinger
101
 
 Attendance:

Dan
Bower,
Luke
Boosey
(minutes),
Jelena
Culic‐Viskota,
Maggie
 Osburn,
Megan
Dobro,
Terry
G

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Source URL: gsc.caltech.edu

Language: English - Date: 2011-08-17 18:18:23
112Computer vision / Statistical classification / Linear classifier / Caltech 101 / Pattern recognition / Supervised learning / Support vector machine / Yann LeCun / Unsupervised learning / Machine learning / Statistics / Artificial intelligence

What is the Best Multi-Stage Architecture for Object Recognition? Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio Ranzato and Yann LeCun The Courant Institute of Mathematical Sciences New York University, 715 Broadway,

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Source URL: cs.nyu.edu

Language: English - Date: 2009-07-16 09:28:03
113Statistical classification / Error detection and correction / Yann LeCun / Linear classifier / Matching pursuit / Supervised learning / Unsupervised learning / Caltech 101 / Support vector machine / Statistics / Artificial intelligence / Machine learning

Learning Convolutional Feature Hierarchies for Visual Recognition Koray Kavukcuoglu1 , Pierre Sermanet1 , Y-Lan Boureau2,1 , Karol Gregor1 , Micha¨el Mathieu1 , Yann LeCun1 1

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Source URL: yann.lecun.com

Language: English - Date: 2010-11-26 14:15:40
114Computer vision / Statistical classification / Linear classifier / Caltech 101 / Pattern recognition / Supervised learning / Support vector machine / Yann LeCun / Unsupervised learning / Machine learning / Statistics / Artificial intelligence

What is the Best Multi-Stage Architecture for Object Recognition? Kevin Jarrett, Koray Kavukcuoglu, Marc’Aurelio Ranzato and Yann LeCun The Courant Institute of Mathematical Sciences New York University, 715 Broadway,

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Source URL: yann.lecun.com

Language: English - Date: 2009-08-05 19:17:47
115Science / Computational neuroscience / Yann LeCun / Supervised learning / Artificial neural network / Caltech 101 / Unsupervised learning / Backpropagation / Pattern recognition / Machine learning / Artificial intelligence / Neural networks

Convolutional Networks and Applications in Vision Yann LeCun, Koray Kavukcuoglu and Cl´ement Farabet Computer Science Department, Courant Institute of Mathematical Sciences, New York University {yann,koray,cfarabet}@cs.

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Source URL: pub.clement.farabet.net

Language: English - Date: 2013-07-18 17:55:30
116Science / Computational neuroscience / Yann LeCun / Supervised learning / Artificial neural network / Caltech 101 / Unsupervised learning / Backpropagation / Pattern recognition / Machine learning / Artificial intelligence / Neural networks

Convolutional Networks and Applications in Vision Yann LeCun, Koray Kavukcuoglu and Cl´ement Farabet Computer Science Department, Courant Institute of Mathematical Sciences, New York University {yann,koray,cfarabet}@cs.

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Source URL: yann.lecun.com

Language: English - Date: 2010-05-10 11:37:38
117Computational 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 [removed] [removed] [removed]

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Source URL: static.googleusercontent.com

Language: English - Date: 2012-07-12 02:17:19
118Artificial intelligence / Brain / Object recognition / Caltech 101 / Visual cortex / Feature vector / Visual system / Shape context / Kadir–Brady saliency detector / Computer vision / Vision / Optics

Comparing State-of-the-Art Visual Features on Invariant Object Recognition Tasks Nicolas Pinto1 , Youssef Barhomi1 , David D. Cox2 , and James J. DiCarlo1 1 Massachusetts Institute of Technology, Cambridge, MA, U.S.A 2

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Source URL: pinto.scripts.mit.edu

Language: English - Date: 2010-11-15 19:10:14
119Statistical classification / Error detection and correction / Yann LeCun / Linear classifier / Matching pursuit / Supervised learning / Unsupervised learning / Caltech 101 / Support vector machine / Statistics / Artificial intelligence / Machine learning

Learning Convolutional Feature Hierarchies for Visual Recognition Koray Kavukcuoglu1 , Pierre Sermanet1 , Y-Lan Boureau2,1 , Karol Gregor1 , Micha¨el Mathieu1 , Yann LeCun1 1

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Source URL: deeplearning.cs.cmu.edu

Language: English - Date: 2013-10-24 15:10:40
120Computational 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 [removed] [removed] [removed]

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Source URL: static.googleusercontent.com

Language: English - Date: 2012-07-12 02:17:19
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