G-Softmax: Improving Intraclass Compactness and Interclass Separability of Features
10.1109/tnnls.2019.2909737
Saved in:
Main Authors: | Luo, Yan, Wong, Yongkang, Kankanhalli, Mohan, Zhao, Qi |
---|---|
Other Authors: | INTERACTIVE & DIGITAL MEDIA INSTITUTE |
Format: | Article |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2019
|
Online Access: | https://scholarbank.nus.edu.sg/handle/10635/157067 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Similar Items
-
Joint weakly supervised image emotion analysis based on interclass discrimination and intraclass correlation
by: ZHANG, Xinyue, et al.
Published: (2024) -
The effect of softmax temperature on recent knowledge distillation algorithms
by: Poh, Dominique
Published: (2023) -
An interclass margin maximization learning algorithm for evolving spiking neural network
by: Dora, Shirin, et al.
Published: (2021) -
Direction Concentration Learning: Enhancing Congruency in Machine Learning
by: Luo, Yan, et al.
Published: (2020) -
A novel electrocardiogram arrhythmia classification method based on stacked sparse auto-encoders and softmax regression
by: Yang, Jianli, et al.
Published: (2020)