Semi-FCMNet: Semi-Supervised Learning for Forest Cover Mapping from Satellite Imagery via Ensemble Self-Training and Perturbation

Semi-FCMNet: Semi-Supervised Learning for Forest Cover Mapping from Satellite Imagery via Ensemble Self-Training and Perturbation

Forest cover mapping is of paramount importance for environmental monitoring, biodiversity assessment, and forest resource management. In the realm of forest cover mapping, significant advancements have been made by leveraging fully supervised semantic segmentation models. However, the process of ac...

Full description

Bibliographic Details
Main Authors: Beiqi Chen, Liangjing Wang, Xijian Fan, Weihao Bo, Xubing Yang, Tardi Tjahjadi
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Remote Sensing
Subjects:
semi-supervision
forest cover mapping
semi-supervised semantic segmentation
self-training
Online Access:https://www.mdpi.com/2072-4292/15/16/4012

Similar Items

Similar Items