Data-specific activation function learning for hyperspectral image classification

Yu Li, Wei Wei, Jinyang Zhang, Lei Zhang, Yanning Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

2 引用 (Scopus)

摘要

Hyperspectral image (HSI) classification plays an important role in lots of HSI analysis related tasks. In recent years, deep learning based methods draw much attention for HSI classification due to the powerful representation ability. The activation function is essential for deep learning based methods since it introduces nonlinearity into the network. However, existing activation functions such as Sigmoid and ReLU are pre-defined, which are handcrafted and general for any kinds of data. If they fit well to a specific dataset and thus lead to best classification result is seldom studied. In this paper, we propose to learn a specific data-driven function called data-specific (DS) activation function for HSI classification. Instead of using a hand-crafted function, we propose an HSI oriented activation function generation strategy, in which neural network (NN) architecture is utilized to learn the activation function suitable for HSI classification. Experiment results demonstrate the effectiveness of the learned activation function for HSI classification.

源语言英语
主期刊名2020 8th International Conference on Orange Technology, ICOT 2020
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9781665418522
DOI
出版状态已出版 - 18 12月 2020
活动8th International Conference on Orange Technology, ICOT 2020 - Daegu, 韩国
期限: 18 12月 202021 12月 2020

出版系列

姓名2020 8th International Conference on Orange Technology, ICOT 2020

会议

会议8th International Conference on Orange Technology, ICOT 2020
国家/地区韩国
Daegu
时期18/12/2021/12/20

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