CHAINLETS: A NEW DESCRIPTOR FOR DETECTION AND RECOGNITION
Detecting and recognizing objects in images is one of the most challenging tasks in computer vision, as it seeks to detect subtle objects while ignoring massive numbers of negatives. While deep networks have led to advances in many problems, new representations and approaches are needed for applications without millions of training samples or where explanations are required. This thesis focuses on a new representation that can be used for detection/recognition in many applications of computer vision, and demonstrates it on two very different applications: pedestrian detection and ear ...
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