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WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
In this paper, we introduce a novel framework for WEakly supervised Learning of Deep cOnvolutional neural Networks (WELDON). Our method is dedicated to automatically selecting relevant image regions from weak annotations, e.g. global image labels, and encompasses the following contributions. Firstly, WELDON leverages recent improvements on the Multiple Instance Learning paradigm, i.e. negative evidence scoring and top instance selection. Secondly, the deep CNN is trained to optimize Average
doi:10.1109/cvpr.2016.513
dblp:conf/cvpr/DurandTC16
fatcat:2mqnc6l7jzhmhgjr55vispq4he