Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification

Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification

Recent research in deep Convolutional Neural Networks(CNN) faces the challenges of vanishing/exploding gradient issues, training instability, and feature redundancy. Orthogonality Regularization(OR), which introduces a penalty function considering the orthogonality of neural networks, could be a rem...

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Bibliographic Details
Main Authors: Taehyeon Kim, Se-Young Yun
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Deep neural network (DNN)
kernel
orthogonality regularization
convolutional neural network (CNN)
regularization
image classification
Online Access:https://ieeexplore.ieee.org/document/9804718/

Internet

https://ieeexplore.ieee.org/document/9804718/

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