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View all- Hadi AWon K(2024)Deep Convolutional Neural Network Compression based on the Intrinsic Dimension of the Training DataACM SIGAPP Applied Computing Review10.1145/3663652.366365424:1(14-23)Online publication date: 3-May-2024
Deep learning has shown excellent performance in many fields, especially image recognition and retrieval in recent years. The performance of convolutional neural networks (CNNs) is particularly outstanding. CNNs, however, are usually ...
Deep Reinforcement Learning (DRL) uses the best of both Reinforcement Learning and Deep Learning for solving problems which cannot be addressed by them individually. Deep Reinforcement Learning has been used widely for games, robotics etc. Limited work ...
It is of great significance to compress neural network models so that they can be deployed on resource-constrained embedded mobile devices. However, due to the lack of theoretical guidance for non-salient network components, existing model ...
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