Detection and Correction of Mislabeled Training Samples for Hyperspectral Image Classification.
IEEE Transactions on Geoscience and Remote Sensing(2018)
摘要
In this paper, a novel method is introduced to detect and correct mislabeled training samples for hyperspectral image classification. First, domain transform recursive filtering-based feature extraction is used to improve the separability of the training samples. Then, constrained energy minimization-based object detection is performed on the training set with each training sample serving as the o...
更多查看译文
关键词
Hyperspectral imaging,Training,Feature extraction,Transforms,Object detection,Image edge detection
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要