Data-Aware Adaptive Pruning Model Compression Algorithm Based on a Group Attention Mechanism and Reinforcement Learning

The success of convolutional neural networks (CNNs) benefits from the stacking of convolutional layers, which improves the model's receptive field for image data but also causes a decrease in inference speed. To improve the inference speed of large convolutional network models without sacrifici...

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Veröffentlicht in:	IEEE access Jg. 10; S. 82396 - 82406
Hauptverfasser:	Yang, Zhi, Zhai, Yuan, Xiang, Yi, Wu, Jianquan, Shi, Jinliang, Wu, Ying
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptive algorithms Aircraft performance Algorithms Artificial neural networks attention mechanism Computational modeling Convolutional neural networks Datasets Filtering algorithms Inference Machine learning Model compression pruning algorithm Reinforcement learning Training data
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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