Cargando…
AresB-Net: accurate residual binarized neural networks using shortcut concatenation and shuffled grouped convolution
This article proposes a novel network model to achieve better accurate residual binarized convolutional neural networks (CNNs), denoted as AresB-Net. Even though residual CNNs enhance the classification accuracy of binarized neural networks with increasing feature resolution, the degraded classifica...
Autor principal: | Kim, HyunJin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8022573/ https://www.ncbi.nlm.nih.gov/pubmed/33834112 http://dx.doi.org/10.7717/peerj-cs.454 |
Ejemplares similares
-
PresB-Net: parametric binarized neural network with learnable activations and shuffled grouped convolution
por: Shin, Jungwoo, et al.
Publicado: (2022) -
EmotionNet Nano: An Efficient Deep Convolutional Neural Network Design for Real-Time Facial Expression Recognition
por: Lee, James Ren, et al.
Publicado: (2021) -
Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression From Chest CT Images
por: Wong, Alexander, et al.
Publicado: (2021) -
TB-Net: A Tailored, Self-Attention Deep Convolutional Neural Network Design for Detection of Tuberculosis Cases From Chest X-Ray Images
por: Wong, Alexander, et al.
Publicado: (2022) -
Deep convolutional neural networks for regular texture recognition
por: Liu, Ni, et al.
Publicado: (2022)