An Impartial Semi-Supervised Learning Strategy for Imbalanced Classification on VHR Images

An Impartial Semi-Supervised Learning Strategy for Imbalanced Classification on VHR Images

Imbalanced learning is a common problem in remote sensing imagery-based land-use and land-cover classifications. Imbalanced learning can lead to a reduction in classification accuracy and even the omission of the minority class. In this paper, an impartial semi-supervised learning strategy based on...

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Bibliographic Details
Main Authors: Fei Sun, Fang Fang, Run Wang, Bo Wan, Qinghua Guo, Hong Li, Xincai Wu
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
image classification
class imbalance
impartial semi-supervised learning strategy (ISS)
extreme gradient boosting (XGB)
very-high-resolution (VHR)
Online Access:https://www.mdpi.com/1424-8220/20/22/6699

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