A Joint Network for Low-Light Image Enhancement Based on Retinex
Sign Up to like & getrecommendations! Published in 2024 at "Cognitive Computation"
DOI: 10.1007/s12559-024-10347-4
Abstract: Methods based on the physical Retinex model are effective in enhancing low-light images, adeptly handling the challenges posed by low signal-to-noise ratios and high noise in images captured under weak lighting conditions. However, traditional models… read more here.
Keywords: light image; low light; joint network; retinex ... See more keywords
JONNEE: Joint Network Nodes and Edges Embedding
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3122100
Abstract: Recently, graph embedding models significantly improved the quality of graph machine learning tasks, such as node classification and link prediction. In this work, we propose a model called JONNEE (JOint Network Nodes and Edges Embedding),… read more here.
Keywords: nodes edges; network nodes; graph; edges embedding ... See more keywords
A Joint Network of Super-Resolution and Active Learning for Agricultural Land Classification
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2024.3432976
Abstract: Remote sensing image analysis plays a vital role in achieving intelligent agricultural monitoring. However, the acquisition of high-resolution agricultural remote sensing data can be resource-intensive, resulting in an imbalance between training samples and artificial intelligence… read more here.
Keywords: agricultural land; joint network; remote sensing; resolution ... See more keywords