Cargando…
A new lightweight deep neural network for surface scratch detection
This paper aims to develop a lightweight convolutional neural network, WearNet, to realise automatic scratch detection for components in contact sliding such as those in metal forming. To this end, a large surface scratch dataset obtained from cylinder-on-flat sliding tests was used to train the Wea...
Autores principales: | Li, Wei, Zhang, Liangchi, Wu, Chuhan, Cui, Zhenxiang, Niu, Chao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer London
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9596349/ https://www.ncbi.nlm.nih.gov/pubmed/36313192 http://dx.doi.org/10.1007/s00170-022-10335-8 |
Ejemplares similares
-
A lightweight deep neural network with higher accuracy
por: Zhao, Liquan, et al.
Publicado: (2022) -
Fast and Accurate Object Detection in Remote Sensing Images Based on Lightweight Deep Neural Network
por: Lang, Lei, et al.
Publicado: (2021) -
Accurate brain age prediction with lightweight deep neural networks
por: Peng, Han, et al.
Publicado: (2021) -
Lightweight Deep Neural Network Embedded with Stochastic Variational Inference Loss Function for Fast Detection of Human Postures
por: Hsu, Feng-Shuo, et al.
Publicado: (2023) -
Deep Learning in Drug Discovery and Medicine; Scratching the Surface
por: Dana, Dibyendu, et al.
Publicado: (2018)