IEEE_TGRS_PDBSNet and IEEE_TGRS_DirectNet
About IEEE_TGRS_PDBSNet
DegangWang97/IEEE_TGRS_PDBSNet
[TGRS 2023 ESI Highly Cited Paper (TOP 1%)] PDBSNet: Pixel-Shuffle Downsampling Blind-Spot Reconstruction Network for Hyperspectral Anomaly Detection
This tool helps geospatial analysts and remote sensing specialists identify unusual or unexpected objects within hyperspectral satellite imagery. You input a hyperspectral image, and it outputs an 'anomaly score' map, highlighting pixels that deviate significantly from their surroundings. This is particularly useful for tasks like environmental monitoring or defense applications where spotting irregularities is critical.
About IEEE_TGRS_DirectNet
DegangWang97/IEEE_TGRS_DirectNet
[TGRS 2024 ESI Highly Cited Paper (TOP 1%)] Sliding Dual-Window-Inspired Reconstruction Network for Hyperspectral Anomaly Detection
This tool helps geospatial analysts and remote sensing specialists pinpoint unusual objects or features in satellite and airborne hyperspectral images. You provide an unlabeled hyperspectral image, and it outputs a map highlighting areas that deviate significantly from their surroundings. This is ideal for identifying anomalies like unexpected geological formations, environmental changes, or specific target detection.
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