35 citations · 35 across the 4 of their papers we have counts for
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cs.CV2026
Any Model, Any Place, Any Time: Get Remote Sensing Foundation Model Embeddings On Demand
Dingqi Ye, Daniel Kiv, Wei Hu +2
The remote sensing community is witnessing a rapid growth of foundation models, which provide powerful embeddings for a wide range of downstream tasks. However, practical adoption…
cs.CV2025
SFNet: Fusion of Spatial and Frequency-Domain Features for Remote Sensing Image Forgery Detection
Ji Qi, Xinchang Zhang, Dingqi Ye +4
The rapid advancement of generative artificial intelligence is producing fake remote sensing imagery (RSI) that is increasingly difficult to detect, potentially leading to erroneou…
cs.CV2023★ 35 cited
OBSUM: An object-based spatial unmixing model for spatiotemporal fusion of remote sensing images
Houcai Guo, Dingqi Ye, Lorenzo Bruzzone
Spatiotemporal fusion aims to improve both the spatial and temporal resolution of remote sensing images, thus facilitating time-series analysis at a fine spatial scale. However, th…