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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Bibliographic Details
Published in:	Neural computing & applications Vol. 34; no. 6; pp. 4889 - 4903
Main Authors:	Choudhary, Tejalal, Mishra, Vipul, Goswami, Anurag, Sarangapani, Jagannathan
Format:	Journal Article
Language:	English
Published:	London Springer London 01.03.2022 Springer Nature B.V
Subjects:	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 Access:	Get full text
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