Cargando…
Image Representation Method Based on Relative Layer Entropy for Insulator Recognition
Deep convolutional neural networks (DCNNs) with alternating convolutional, pooling and decimation layers are widely used in computer vision, yet current works tend to focus on deeper networks with many layers and neurons, resulting in a high computational complexity. However, the recognition task is...
Autores principales: | Zhao, Zhenbing, Qi, Hongyu, Fan, Xiaoqing, Xu, Guozhi, Qi, Yincheng, Zhai, Yongjie, Zhang, Ke |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516894/ https://www.ncbi.nlm.nih.gov/pubmed/33286193 http://dx.doi.org/10.3390/e22040419 |
Ejemplares similares
-
Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition
por: Jia, Qi, et al.
Publicado: (2015) -
Insulator Umbrella Disc Shedding Detection in Foggy Weather
por: Xin, Rui, et al.
Publicado: (2022) -
Multiscale Entropy Feature Extraction Method of Running Power Equipment Sound
por: Zhai, Yongjie, et al.
Publicado: (2020) -
Multi-Geometric Reasoning Network for Insulator Defect Detection of Electric Transmission Lines
por: Zhai, Yongjie, et al.
Publicado: (2022) -
Entropy-Based Image Fusion with Joint Sparse Representation and Rolling Guidance Filter
por: Liu, Yudan, et al.
Publicado: (2020)