BMW / GPU / Volkswagen / Isuzu / Honda / Toyota / Ford / Rolls-Royce / Suzuki / Yahoo! / CNN / using CNN / / /
Facility
Stanford University / Interactively building / California Institute of Technology / University of Michigan / /
IndustryTerm
non-rigid neural network / neural networks / overall car classification / recognition algorithm / part discovery algorithm / car models / convolutional neural network / deep convolutional neural networks / target car / energy / Car classification accuracy / ultimate solution / bank / convolutional neural networks / convolutional deep belief networks / high energy / computing / learned using a convolutional neural network / /
Organization
California Institute of Technology / Ensemble of Localized Learned Features Fig / Ensemble of Localized Learned Features / University of Michigan / U.S. Securities and Exchange Commission / UCSD / Stanford University / Ensemble of Parts / /
Person
Y. Chai / V / Jia Li / N. Zhang / V / V. Lempitsky / A. Zisserman / L. Van Gool / E. Nilsback / C. Rother / V / Jia Deng / E. Rahtu / V / Jonathan Krause / /
Position
tackle / Fisher / /
Product
Chevrolet Silverado / Land Rover LR2 / Hummer H2 SUT / Ford F-150 / Spyker C8 / Suzuki SX4 / BMW 3 / BMW Z4 / Aston Martin V8 / /
Learning Features and Parts for Fine-Grained Recognition (Invited Paper) Jonathan Krause∗ , Timnit Gebru∗ , Jia Deng † , Li-Jia Li ‡ , Li Fei-Fei∗ ∗