Filter pruning generally follows a structured pruning method, which helps the models preserve the network structure. Moreover, filter pruning directly reduces the convolution operations, and the reduction of convolution operations greatly improves the performance of the CNN model.
Dec 7, 2023
Dec 7, 2023 · The experimental results show that among the four filter pruning methods, the soft filter pruning method best preserves the accuracy of the ...
Empirical evaluation of filter pruning methods for acceleration of convolutional neural network. Authors. Kumar, Dheeraj; Mehta, Mayuri A.; Joshi, Vivek C ...
Empirical evaluation of filter pruning methods for acceleration of convolutional neural network. Authors. Kumar, Dheeraj; Mehta, Mayuri A.; Joshi, Vivek C ...
Empirical evaluation of filter pruning methods for acceleration of convolutional neural network ... Authors: Dheeraj Kumar; Mayuri A. Mehta; Vivek C. Joshi ...
Article "Empirical evaluation of filter pruning methods for acceleration of convolutional neural network" Detailed information of the J-GLOBAL is an ...
Mar 6, 2024 · The neural network pruning methods are categorized into structured pruning and unstructured pruning based on whether the pruning preserves the ...
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This paper proposed a Soft Filter Pruning (SFP) method to accelerate the inference procedure of deep Convolutional Neural Networks (CNNs).
The process flow of LFPC · Empirical evaluation of filter pruning methods for acceleration of convolutional neural network. Article. Full-text available. Dec ...
This paper proposed a Soft Filter Pruning (SFP) method to accelerate the inference procedure of deep Convolutional Neural Networks (CNNs).
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