Pruning Convolution Neural Network (SqueezeNet) for Efficient Hardware Deployment
Indiana University-Purdue University Indianapolis (IUPUI) === In recent years, deep learning models have become popular in the real-time embedded application, but there are many complexities for hardware deployment because of limited resources such as memory, computational power, and energy. Recent...
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Language: | en_US |
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2018
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Online Access: | http://hdl.handle.net/1805/17923 |