| Document Date: 2014-07-09 13:23:14
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City Pittsburgh / / Company Amazon / / Country Switzerland / Belgium / / / Facility To mine / / IndustryTerm component-mining algorithms / food dataset / food items / Food images / similar food classes / vision applications / food photography / online photo repositories / rf component mining / part mining / similar food types / discriminative part-mining algorithms / food categories / component mining / real-world food recognition / real-world computer vision algorithms / weakly-supervised mining method / mid-level discriminative patch mining work / discriminative part mining / food recognition / real-world food dataset / component mining approaches / mining / food parts / social networks / recent mining methods / discriminative part mining methods / food category / food type / part-based mining approach / search space / discriminative part mining method / optimized cutting plane algorithm / iterative hard-negative mining / food / mobile food photography / / NaturalFeature Random Forests / Random Forest / / Organization Matthieu Guillaumin1 Luc Van Gool1 / 2 Computer Vision Lab / / Person L. Van Gool Encoding / L. Van Gool / / Position single model for each cluster / using Improved Fisher / / ProgrammingLanguage K / / Technology computer vision algorithms / sliding windows / optimized cutting plane algorithm / discriminative part-mining algorithms / component-mining algorithms / / URL http /
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Food-101 – Mining Discriminative Components with Random Forests Lukas Bossard1 1 Matthieu Guillaumin1