使用带有关注机制的自适应跨资源网 ++ 的有效水下图像增强框架

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Experimental & Theoretical Artificial Intelligence Pub Date : 2024-08-17 DOI:10.1080/0952813x.2024.2383659
S. Meera, Ajanya P
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引用次数: 0

摘要

水下环境错综复杂,光学镜头很难捕捉到没有雾度和色彩失真的清晰水下照片。一些研究利用域适应和转移技术来解决这个问题。
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An effectual underwater image enhancement framework using adaptive trans-resunet ++ with attention mechanism
The intricacy of the underwater setting makes it difficult for optical lenses to capture clear underwater photos without haze and colour distortion. Some studies use domain adaptation and transfer ...
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来源期刊
CiteScore
6.10
自引率
4.50%
发文量
89
审稿时长
>12 weeks
期刊介绍: Journal of Experimental & Theoretical Artificial Intelligence (JETAI) is a world leading journal dedicated to publishing high quality, rigorously reviewed, original papers in artificial intelligence (AI) research. The journal features work in all subfields of AI research and accepts both theoretical and applied research. Topics covered include, but are not limited to, the following: • cognitive science • games • learning • knowledge representation • memory and neural system modelling • perception • problem-solving
期刊最新文献
Occlusive target recognition method of sorting robot based on anchor-free detection network An effectual underwater image enhancement framework using adaptive trans-resunet ++ with attention mechanism An experimental study of sentiment classification using deep-based models with various word embedding techniques Sign language video to text conversion via optimised LSTM with improved motion estimation An efficient safest route prediction-based route discovery mechanism for drivers using improved golden tortoise beetle optimizer
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