Cargando…
Dynamical Conventional Neural Network Channel Pruning by Genetic Wavelet Channel Search for Image Classification
Neural network pruning is critical to alleviating the high computational cost of deep neural networks on resource-limited devices. Conventional network pruning methods compress the network based on the hand-crafted rules with a pre-defined pruning ratio (PR), which fails to consider the variety of c...
Autores principales: | Chen, Lin, Gong, Saijun, Shi, Xiaoyu, Shang, Mingsheng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8578706/ https://www.ncbi.nlm.nih.gov/pubmed/34776916 http://dx.doi.org/10.3389/fncom.2021.760554 |
Ejemplares similares
-
Lossless Reconstruction of Convolutional Neural Network for Channel-Based Network Pruning
por: Lee, Donghyeon, et al.
Publicado: (2023) -
EEG channel selection based on sequential backward floating search for motor imagery classification
por: Tang, Chao, et al.
Publicado: (2022) -
Random pruning: channel sparsity by expectation scaling factor
por: Sun, Chuanmeng, et al.
Publicado: (2023) -
Identification of plant leaf diseases by deep learning based on channel attention and channel pruning
por: Chen, Riyao, et al.
Publicado: (2022) -
Wavelet Packet Feature Assessment for High-Density Myoelectric Pattern Recognition and Channel Selection toward Stroke Rehabilitation
por: Wang, Dongqing, et al.
Publicado: (2016)