Back to Results
First PageMeta Content
Statistics / Image processing / California Institute of Technology / Caltech 101 / Object recognition / Feature selection / Support vector machine / Template matching / Filter / Computer vision / Vision / Imaging


Object class recognition and localization using sparse features with limited receptive fields ∗ Jim Mutch † Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Cambridge, MA
Add to Reading List

Document Date: 2008-04-17 16:44:02

Open Document

File Size: 1,35 MB

Share Result on Facebook

Company

Google / Intel / /

/

Facility

University of British Columbia / Cognitive Sciences Massachusetts Institute of Technology Cambridge / Computer Science University of British Columbia Vancouver / S1 pyramid / /

IndustryTerm

motivated algorithms / computer vision algorithms / computer vision systems / feedforward processing / car dataset / car database / car localization task / image search / neighborhood suppression algorithm / convolutional networks / /

MusicGroup

B.C. / /

Organization

Institute of Technology Cambridge / Computer Science University / MA David G. Lowe Department / Massachusetts Institute of Technology / Department of Brain / University of British Columbia / /

Person

Select / Agarwal / Jim Mutch / David G. Lowe / /

Position

Model / base model / an S2 unit / model for V1 complex cells / /

ProgrammingLanguage

MATLAB / /

ProvinceOrState

British Columbia / /

Technology

neuroscience / Biologically motivated algorithms / computer vision algorithms / scoring algorithm / machine learning / neighborhood suppression algorithm / consolidated using the neighborhood suppression algorithm / /

URL

http /

SocialTag