Cargando…
PlaneNet: an efficient local feature extraction network
Due to memory and computing resources limitations, deploying convolutional neural networks on embedded and mobile devices is challenging. However, the redundant use of the 1 × 1 convolution in traditional light-weight networks, such as MobileNetV1, has increased the computing time. By utilizing the...
Autores principales: | Lin, Bin, Su, Houcheng, Li, Danyang, Feng, Ao, Li, Hongxiang, Li, Jiao, Jiang, Kailin, Jiang, Hongbo, Gong, Xinyao, Liu, Tao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670390/ https://www.ncbi.nlm.nih.gov/pubmed/34977350 http://dx.doi.org/10.7717/peerj-cs.783 |
Ejemplares similares
-
TbsNet: the importance of thin-branch structures in CNNs
por: Hu, Xiujian, et al.
Publicado: (2023) -
Petri Net based modeling and analysis for improved resource utilization in cloud computing
por: Rizwan Ali, Muhammad, et al.
Publicado: (2021) -
GaborNet: investigating the importance of color space, scale and orientation for image classification
por: Rimiru, Richard M., et al.
Publicado: (2022) -
Improved MobileNetV2 crop disease identification model for intelligent agriculture
por: Lu, Jianbo, et al.
Publicado: (2023) -
A study on the classification of stylistic and formal features in English based on corpus data testing
por: Li, Shuhui
Publicado: (2023)