MSG-SR-Net: A Weakly Supervised Network Integrating Multiscale Generation and Superpixel Refinement for Building Extraction From High-Resolution Remotely Sensed Imageries

MSG-SR-Net: A Weakly Supervised Network Integrating Multiscale Generation and Superpixel Refinement for Building Extraction From High-Resolution Remotely Sensed Imageries

Weakly supervised semantic segmentation (WSSS) methods based on image-level labels can relieve the tedious pixel-level annotation burden, and these methods are mainly based on class activation maps (CAMs). However, it is challenging to generate high-quality CAMs for high-resolution remotely sensed i...

Full description

Bibliographic Details
Main Authors: Xin Yan, Li Shen, Jicheng Wang, Xu Deng, Zhilin Li
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Building extraction
class activation map
high-resolution remotely sensed imagery
superpixel refinement
weakly supervised deep learning
Online Access:https://ieeexplore.ieee.org/document/9665252/

Internet

https://ieeexplore.ieee.org/document/9665252/

Similar Items