SPNet: Semantic preserving network with semantic constraint and non-semantic calibration for color constancy-Reference-Cited by-同舟云学术

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SPNet: Semantic preserving network with semantic constraint and non-semantic calibration for color constancy

Published:2024-09 Issue: Volume:596 Page:127947
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Zhang Wen,Li Zhijiang^ORCID,Zhang Li,Tan Zhenshan

Publisher

Elsevier BV

Reference64 articles.

1. Approaching the computational color constancy as a classification problem through deep learning;Oh;Pattern Recognit.,2017

2. Boosting R-CNN: Reweighting R-CNN samples by RPN’s error for underwater object detection;Song;Neurocomputing,2023

3. Evaluation of underwater image enhancement algorithms based on Retinex and its implementation on embedded systems;Aguirre-Castro;Neurocomputing,2022

4. Learning deep texture-structure decomposition for low-light image restoration and enhancement;Zhao;Neurocomputing,2023

5. Low-light image enhancement with knowledge distillation;Li;Neurocomputing,2023

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