Cargando…
Enhanced mechanisms of pooling and channel attention for deep learning feature maps
The pooling function is vital for deep neural networks (DNNs). The operation is to generalize the representation of feature maps and progressively cut down the spatial size of feature maps to optimize the computing consumption of the network. Furthermore, the function is also the basis for the compu...
Autores principales: | Li, Hengyi, Yue, Xuebin, Meng, Lin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9748832/ https://www.ncbi.nlm.nih.gov/pubmed/36532804 http://dx.doi.org/10.7717/peerj-cs.1161 |
Ejemplares similares
-
Infusing Expert Knowledge Into a Deep Neural Network Using Attention Mechanism for Personalized Learning Environments
por: Tato, Ange, et al.
Publicado: (2022) -
Kinship verification and recognition based on handcrafted and deep learning feature-based techniques
por: Nader, Nermeen, et al.
Publicado: (2021) -
Heterogeneous mission planning for a single unmanned aerial vehicle (UAV) with attention-based deep reinforcement learning
por: Jung, Minjae, et al.
Publicado: (2022) -
Semantic visual simultaneous localization and mapping (SLAM) using deep learning for dynamic scenes
por: Zhang, Xiao Ya, et al.
Publicado: (2023) -
Analysis of Features Selected by a Deep Learning Model for Differential Treatment Selection in Depression
por: Mehltretter, Joseph, et al.
Publicado: (2020)