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Deep learning for class-generic object detection
Brody Huval, Adam Coates, Andrew Ng
Dec 25, 2013 (modified: Dec 25, 2013)ICLR 2014 workshop submissionreaders: everyone
Decision:submitted, no decision
Abstract:We investigate the use of deep neural networks for the task of class-generic object detection. We show that neural networks originally designed for image recognition can be trained to detect objects within images, regardless of their class, including objects for which no bounding box labels have been provided. In addition, we show that bounding box labels yield a 1% performance increase on the ImageNet recognition challenge.
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