3 papers
cs.CV2026
FarmMind: Reasoning-Query-Driven Dynamic Segmentation for Farmland Remote Sensing Images
Haiyang Wu, Weiliang Mu, Jipeng Zhang +4
Existing methods for farmland remote sensing image (FRSI) segmentation generally follow a static segmentation paradigm, where analysis relies solely on the limited information cont…
cs.CV2025
A Joint Learning Framework with Feature Reconstruction and Prediction for Incomplete Satellite Image Time Series in Agricultural Semantic Segmentation
Yuze Wang, Mariana Belgiu, Haiyang Wu +3
Satellite Image Time Series (SITS) is crucial for agricultural semantic segmentation. However, Cloud contamination introduces time gaps in SITS, disrupting temporal dependencies an…
cs.CV2025
A large-scale image-text dataset benchmark for farmland segmentation
Chao Tao, Dandan Zhong, Weiliang Mu +2
The traditional deep learning paradigm that solely relies on labeled data has limitations in representing the spatial relationships between farmland elements and the surrounding en…