AutoPruner: An End-to-End Trainable Filter Pruning Method for Efficient Deep Model Inference

标题
AutoPruner: An End-to-End Trainable Filter Pruning Method for Efficient Deep Model Inference
作者
关键词
Neural network pruning, Model compression, CNN acceleration
出版物
PATTERN RECOGNITION
Volume -, Issue -, Pages 107461
出版商
Elsevier BV
发表日期
2020-05-25
DOI
10.1016/j.patcog.2020.107461

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