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Beyond Hard Negative Mining: Efficient Detector Learning via Block-Circulant Decomposition Jo˜ao F. Henriques, Jo˜ao Carreira, Rui Caseiro and Jorge Batista Institute of Systems and Robotics, University of Coimbra {hen
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Document Date: 2014-06-04 23:24:55


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City

F. Durand / Paris / /

Company

Neural Networks / /

/

Event

Product Recall / Product Issues / /

Facility

University of Coimbra / Jorge Batista Institute of Systems / /

IndustryTerm

element-wise product / convolution algorithms / dense search / computer vision algorithms / closed-form solutions / dot-product / proposed translation machinery / hard negative mining / mining / augmented real solution / hard negative mining steps / closed-form solution / iterative hard negative mining / negative mining / dot-products / learning algorithms / hard negative mining rounds / /

MarketIndex

Caltech Pedestrians Detection / Caltech Pedestrian Detection / /

Organization

North Atlantic Treaty Organization / Cambridge university / University of Coimbra / Jorge Batista Institute of Systems and Robotics / MIT / U.S. Securities and Exchange Commission / /

Person

B. Alexe / V / Rui Caseiro / /

Product

rounds / Recall Recall / 0.5 Precision 1 0 0.5 Precision / 0.8 / /

ProgrammingLanguage

MATLAB / DC / /

PublishedMedium

Journal of Machine Learning Research / /

Technology

neuroscience / convolution algorithms / computer vision algorithms / 2 Algorithms / training algorithm / http / Machine Learning / /

URL

www.isr.uc.pt/∼henriques / /

SocialTag