R2VD redefines reconstruction as the origin for residual-guided vector diffusion across PPE, GMP, RSM, and VDI stages to achieve superior anomaly detectability and background suppression on eight datasets.
His research interests include deep learning and pattern recognition, and their applications in hyperspectral image processing
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Beyond Reconstruction: Reconstruction-to-Vector Diffusion for Hyperspectral Anomaly Detection
R2VD redefines reconstruction as the origin for residual-guided vector diffusion across PPE, GMP, RSM, and VDI stages to achieve superior anomaly detectability and background suppression on eight datasets.