.png){kind=icon}
返回
GAN-Based One-Class Classification for Remote-Sensing Image Change Detection
.png){kind=icon}
PRE
AI
DOI：10.1109/LGRS.2021.3066435.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Currently, most of the supervised change detection approaches require a training data set that contains samples from both the changed and the unchanged data. However, under certain condition, such as natural disaster and military attack, the changed data samples are very few or even not available but the unchanged data are abundant. In this letter, we develop a generative adversarial networks (GANs)-based one-class classification (OCC) technique for time series remote-sensing image change detection. The proposed method is only trained with the unchanged data instead of both the changed and unchanged data. To achieve this purpose, first, spatial-spectral features are extracted from the time series remote-sensing images. Second, a GAN model is trained to detect the changes only with the extracted features of unchanged data. Remarkably, to offset the outlier errors caused by the incomplete supervision information provided by unchanged data alone, changed data, instead of unchanged data, are generated to improve power of discriminator. Finally, testing data are classified by the trained discriminator of GAN to produce a binary change map. Experimental results obtained on two optical time series remote-sensing data sets confirmed the effectiveness of our proposed method.
Keyword:
Feature extraction
Remote sensing
Training data
Time series analysis
Training
Gallium nitride
Generators
Change detection
generative adversarial networks (GANs)
one-class classification (OCC)
time series
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
16.4
论文数:
1.0W
被引数:
5.1K
机构
引用论文
Evaluating the efficacy of EMLA in alleviating pain associated with lumbar puncture; comparison of open and double-blinded protocols in children.png)
Pain
PainIF0
PREAI
分享收藏SemiCDNet: A Semisupervised Convolutional Neural Network for Change Detection in High Resolution Remote-Sensing ImagesSemiCDNet: 一种用于高分辨率遥感图像变化检测的半监督卷积神经网络
PREAI
分享收藏Network constraints and multi-objective optimization for one-class classificationNEURAL NETWORKS
NEURAL NETWORKSIF6.3
PREAI
分享收藏
查看更多内容