Le Hu

Comparative Performance Analysis of Mainstream Deep Learning and Vision Foundation Models for Small-Sample Vegetation Segmentation in High-Resolution Remote Sensing Imagery

This research fine-tuned and systematically compared the recently prominent “Segment Anything Model” (SAM) series, along with classic fully supervised models (U-Net, DeepLabV3+), open-vocabulary segmentation models (SegEarth-OV), and instance segmentation models (YOLO11s-seg), helping clarify the performance boundaries...