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Statistics / Computer vision / Ensemble learning / Binary trees / Image processing / Random forest / Object recognition / Feature selection / Segmentation / Machine learning / Artificial intelligence / Decision trees


Combining Randomization and Discrimination for Fine-Grained Image Categorization Bangpeng Yao∗ Aditya Khosla∗ Li Fei-Fei Computer Science Department, Stanford University, Stanford, CA
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Document Date: 2013-09-22 18:20:29


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File Size: 643,81 KB

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City

Reading / SURREY / Cambridge / /

Company

Microsoft / /

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Facility

vs. highway / Stanford University / /

IndustryTerm

feature mining / stateof-the-art algorithms / discriminative feature mining / /

MusicGroup

Ours / /

NaturalFeature

Random Forest Framework Random forest / Random forest / /

Organization

Fine-Grained Image Categorization Bangpeng Yao∗ Aditya Khosla∗ Li Fei-Fei Computer Science Department / U.S. Securities and Exchange Commission / National Science Foundation / Stanford University / UCSD / /

Person

Carsten Rother / PASCAL VOC / Olga Russakovsky / Algorithm / Hao Su / /

Position

bayesian hierarchical model for learning natural scene categories / /

ProgrammingLanguage

PASCAL / /

SportsLeague

Stanford University / /

Technology

child Algorithm / Dense Sampling Space Our algorithm / stateof-the-art algorithms / /

URL

http /

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