Distilling the Knowledge of Multiscale Densely Connected Deep Networks in Mechanical Intelligent Diagnosis
At present, deep neural network (DNN) technology is often used in intelligent diagnosis research. However, the huge amount of calculation of DNN makes it difficult to apply in industrial practice. In this paper, an advanced multiscale dense connection deep network MSDC-NET is designed. A well-design...
Main Authors: | Xiaochuan Wang, Aiguo Chen, Liang Zhang, Yi Gu, Mang Xu, Haoyuan Yan |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2021-01-01
|
Series: | Wireless Communications and Mobile Computing |
Online Access: | http://dx.doi.org/10.1155/2021/4319074 |
Similar Items
-
Densely Connected Multiscale Attention Network for Hyperspectral Image Classification
by: Hongmin Gao, et al.
Published: (2021-01-01) -
Fully Dense Multiscale Fusion Network for Hyperspectral Image Classification
by: Zhe Meng, et al.
Published: (2019-11-01) -
A Densely Connected End-to-End Neural Network for Multiscale and Multiscene SAR Ship Detection
by: Jiao Jiao, et al.
Published: (2018-01-01) -
Knowledge distillation in deep learning and its applications
by: Abdolmaged Alkhulaifi, et al.
Published: (2021-04-01) -
Deep and Densely Connected Networks for Classification of Diabetic Retinopathy
by: Hamza Riaz, et al.
Published: (2020-01-01)