Caltech 101

Results: 132



#Item
11Image processing / Feature detection / Computer vision / Generalised Hough transform / Shape context / Image segmentation / K-means clustering / Outline of object recognition / Constellation model / Centroid / Edge detection / Caltech 101

IEEE TRANSACTIONS OF PATTERN ANALYSIS AND MACHINE INTELLIGENCE 1 Multi-Scale Categorical Object Recognition Using Contour Fragments

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Source URL: jamie.shotton.org

Language: English - Date: 2013-04-10 20:20:44
12Image segmentation / One-shot learning / Boosting / Caltech 101 / Conference on Computer Vision and Pattern Recognition / Outline of object recognition / Constellation model / Longuet-Higgins Prize

Efficiently Combining Contour and Texture Cues for Object Recognition Jamie Shotton† Andrew Blake† Roberto Cipolla∗ † Microsoft Research Cambridge

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Source URL: jamie.shotton.org

Language: English - Date: 2013-04-10 20:14:40
13Computational neuroscience / Object recognition / Face detection / Object detection / Serengeti National Park / Part-based models / Neural network / Computer vision / California Institute of Technology / Caltech 101

Project Ideas Fine-grained Categorization of Wild Animals ‘in the Wild’  Build a web demo for fine-grained categorization of animals and/or their activities. You can consider a subset of images and classes of the

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Source URL: rogerioferis.com

Language: English - Date: 2014-02-07 23:32:21
14Neural networks / Learning / Statistical classification / Pattern recognition / Supervised learning / Autoencoder / Unsupervised learning / Caltech 101 / Support vector machine / Machine learning / Statistics / Artificial intelligence

Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition Marc’Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau, Yann LeCun Courant Institute of Mathematical Sciences, New York Universi

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Source URL: www.cs.toronto.edu

Language: English - Date: 2009-08-08 18:43:08
15Automatic image annotation / Dimension reduction / Content-based image retrieval / Feature selection / Caltech 101 / Computer vision / Artificial intelligence / Artificial intelligence applications

Deep Representations and Codes for Image Auto-Annotation Csaba Szepesv´ari Department of Computing Science University of Alberta Edmonton, AB, Canada

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Source URL: www.cs.toronto.edu

Language: English - Date: 2013-12-26 22:59:51
16

Making Visual Object Categorization More Challenging: Randomized Caltech-101 Data Set Teemu Kinnunen, Joni-Kristian Kamarainen∗ , Lasse Lensu, Jukka Lankinen∗ , Heikki K¨alvi¨ainen Machine Vision and Pattern Recogn

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Source URL: personal.lut.fi

- Date: 2011-05-10 10:20:06
    17

    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: 2014-09-19 22:02:44
      18

      Minutes
for
GSC
BoD
Meeting,
Wednesday
April
6th,
2011
–
Schlinger
101
 
 Attendance:

Artemis
Ailianou,
Jai
Shanata,
Milo
Lin,
Paul
Nelson,
Jacob
Sendowski,
 Gloria


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      Source URL: gsc.caltech.edu

      Language: English - Date: 2014-09-19 22:02:44
        19

        BoD  Meeting  –  Wednesday,  July  6th  2011,  12  noon,  101  Schlinger     Attendance  –  Allison  Kunz,  Luke  Boosey  (minutes),  Terry  Gdoutos,  P

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        Source URL: gsc.caltech.edu

        Language: English - Date: 2014-09-19 22:02:44
          20

          Agenda for BoD meeting , 12:00 noon, Wednesday March,Schlinger 101. Attendance: Patrick Sanan, Luke Boosey (minutes), Jelena Culic-Viskota, Jai Shanata, Jacob Sendowski, Milo Lin, Terry Gdoutos, Jose MendozaCortes

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          Source URL: gsc.caltech.edu

          Language: English - Date: 2014-09-19 22:02:44
            UPDATE