Heuristic-based automatic pruning of deep neural networks

The performance of a deep neural network (deep NN) is dependent upon a significant number of weight parameters that need to be trained which is a computational bottleneck. The growing trend of deeper architectures poses a restriction on the training and inference scheme on resource-constrained devic...

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Veröffentlicht in:	Neural computing & applications Jg. 34; H. 6; S. 4889 - 4903
Hauptverfasser:	Choudhary, Tejalal, Mishra, Vipul, Goswami, Anurag, Sarangapani, Jagannathan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.03.2022 Springer Nature B.V
Schlagworte:	Artificial Intelligence Artificial neural networks Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Datasets Image Processing and Computer Vision Inference Neural networks Original Article Parameters Probability and Statistics in Computer Science Pruning Deep neural network Filter pruning Convolutional neural network Efficient inference Model compression and acceleration
ISSN:	0941-0643, 1433-3058
Online-Zugang:	Volltext
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