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7 papers
Geospatial Foundation Models to Enable Progress on Sustainable Development Goals
Pedram Ghamisi, Weikang Yu, Xiaokang Zhang +5
Foundation Models (FMs) are large-scale, pre-trained artificial intelligence (AI) systems that have revolutionized natural language processing and computer vision, and are now adva…
SIGMAE: A Spectral-Index-Guided Foundation Model for Multispectral Remote Sensing
Xiaokang Zhang, Bo Li, Chufeng Zhou +2
Pretraining and fine-tuning have emerged as a new paradigm in remote sensing image interpretation. Among them, Masked Autoencoder (MAE)-based pretraining stands out for its strong…
FarSLIP: Discovering Effective CLIP Adaptation for Fine-Grained Remote Sensing Understanding
Zhenshi Li, Weikang Yu, Dilxat Muhtar +4
As CLIP's global alignment limits its ability to capture fine-grained details, recent efforts have focused on enhancing its region-text alignment. However, current remote sensing (…
EuroMineNet: A Multitemporal Sentinel-2 Benchmark for Spatiotemporal Mining Footprint Analysis in the European Union (2015-2024)
Weikang Yu, Vincent Nwazelibe, Xianping Ma +4
Mining activities are essential for industrial and economic development, but remain a leading source of environmental degradation, contributing to deforestation, soil erosion, and…
DOFA-CLIP: Multimodal Vision-Language Foundation Models for Earth Observation
Zhitong Xiong, Yi Wang, Weikang Yu +7
Earth observation (EO) spans a broad spectrum of modalities, including optical, radar, multispectral, and hyperspectral data, each capturing distinct environmental signals. However…
Auto-Prompting SAM for Weakly Supervised Landslide Extraction
Jian Wang, Xiaokang Zhang, Xianping Ma +2
Weakly supervised landslide extraction aims to identify landslide regions from remote sensing data using models trained with weak labels, particularly image-level labels. However,…