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Saliency detection aims to highlight the most relevant objects in an image. Methods using conventional models struggle whenever salient objects are pictured on top of a cluttered background while deep neural nets suffer from excess complexity and slow evaluation speeds. In this paper, we propose a simplified convolutional neural network which combines local and global information through a multi-resolution...
Sparsity in the weights of deep convolutional networks presents a tremendous opportunity to reduce computational requirements. In order to optimize flow of traffic systems, any viable solution must be able to operate at real-time. Existing computation frameworks do not yet realize the full potential speedup afforded by sparse neural networks. Meanwhile, the power consumption for a GPU is too great...
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