Green environmental security refers to the state of human-environment interactions that
include reducing resource shortages, pollution, and biological dangers that can cause …

Remote sensing is stepping into the era of the foundation model, where the fine-tuning
paradigm is widely adopted to transfer the profound knowledge of pretrained foundation …

Smoke detection is essential for disaster management and timely response to fires.
However, popular deep learning-based algorithms ignore key traditional features such as …

With the advancement of remote sensing technology, the amount of remote sensing image
(RSI) has increased sharply. The explosion in data volume requires higher standards of …

Semantic segmentation is a crucial step in the intelligent interpretation of high-resolution
remote sensing images (HRSIs). Convolutional neural networks and transformers are widely …

In the derection of remote sensing (RS) image analysis, semantic segmentation, as an
important technology, is of key significance for the identification and analysis of land surface …

UAV orthoimages and digital surface models (DSMs) can provide valuable insights for
semantic segmentation methods in comprehending gully erosion (GE) from diverse …

Semantic segmentation plays a vital role in the intelligent comprehension of remote sensing
images (RSIs). However, research on semantic segmentation of RSIs still faces the following …

The fusion of global contextual information with local cropped block details is crucial for
segmenting ultra-high resolution images. In this study, A novel fusion mechanism termed …

This research aims to investigate the challenges of using black box models in deep learning
and analyzing satellite images through a thorough meta-analysis. The main goal of the study …