Graph-based saliency detection using a learning joint affinity matrix
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.03.131
Abstract: Abstract The graph model is a reliable propagation mechanism in saliency detection, saliency value propagation diffusion results between any two nodes are determined merely by defining an effect affinity matrix. Most existing methods generally calculamatrix… read more here.
Keywords: learning joint; affinity; joint affinity; saliency ... See more keywords
An Adaptive Affinity Matrix Optimization for Locality Preserving Projection via Heuristic Methods for Hyperspectral Image Analysis
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2019.2947355
Abstract: Locality preserving projection (LPP) has been often used as a dimensionality reduction tool for hyperspectral image analysis especially in the context of classification since it provides a projection matrix for embedding test samples to low… read more here.
Keywords: heat kernel; locality preserving; projection; affinity matrix ... See more keywords
Flexible Manifold Learning With Optimal Graph for Image and Video Representation
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2018.2810515
Abstract: Graph-based dimensionality reduction techniques have been widely and successfully applied to clustering and classification tasks. The basis of these algorithms is the constructed graph which dictates their performance. In general, the graph is defined by… read more here.
Keywords: image; affinity matrix; manifold learning; flexible manifold ... See more keywords