Deep Classification with Linearity-Enhanced Logits to Softmax Function
Recently, there has been a rapid increase in deep classification tasks, such as image recognition and target detection. As one of the most crucial components in Convolutional Neural Network (CNN) architectures, softmax arguably encourages CNN to achieve better performance in image recognition. Under...
Main Authors: | Hao Shao, Shunfang Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-04-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/25/5/727 |
Similar Items
-
Hardware Implementation of a Softmax-Like Function for Deep Learning
by: Ioannis Kouretas, et al.
Published: (2020-08-01) -
Dimensional Lifting through the Generalized Gram–Schmidt Process
by: Hans Havlicek, et al.
Published: (2018-04-01) -
Whitening Technique Based on Gram–Schmidt Orthogonalization for Motor Imagery Classification of Brain–Computer Interface Applications
by: Hojong Choi, et al.
Published: (2022-08-01) -
LinCos-Softmax: Learning Angle-Discriminative Face Representations With Linearity-Enhanced Cosine Logits
by: Wei-Feng Ou, et al.
Published: (2020-01-01) -
Linear System Solving Scheme Based on Homomorphic Encryption
by: LYU You, WU Wen-yuan
Published: (2022-03-01)