Hierarchical sparse Bayesian learning with adaptive Laplacian prior for single image super-resolution
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-20115-5
Abstract: Single-image super-resolution (SISR) continues to face difficulties in reconstructing perceptually critical details from degraded low-resolution observations. While conventional Bayesian approaches utilizing Relevance Vector Machines (RVMs) provide probabilistic interpretations, their reliance on fixed blur kernel definitions… read more here.
Keywords: resolution; image super; single image; super resolution ... See more keywords
A Weight-Adaptive Laplacian Embedding for Graph-Based Clustering
Sign Up to like & getrecommendations! Published in 2017 at "Neural Computation"
DOI: 10.1162/neco_a_00973
Abstract: Graph-based clustering methods perform clustering on a fixed input data graph. Thus such clustering results are sensitive to the particular graph construction. If this initial construction is of low quality, the resulting clustering may also… read more here.
Keywords: graph based; adaptive laplacian; data graph; graph ... See more keywords