Infrared and Visible Image Fusion Network Based on Self-Compensating Lightweight Convolution

Deep learning has significantly improved the quality of infrared and visible image fusion. However, existing mainstream deep fusion networks often come with complex architectures and a large number of parameters. While general lightweight techniques can effectively reduce model complexity, they ofte...

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Главные авторы:	Ruolin Li, Hongmei Wang, Qiaorong Wu, Cheng Liang, Haoyu Li, Jingyu Wang
Формат:	Artigo
Язык:	Inglês
Опубликовано:	MDPI AG 2026-06-01
Серии:	Sensors
Предметы:	image fusion model lightweighting convolutional neural networks depthwise separable convolution
Online-ссылка:	https://www.mdpi.com/1424-8220/26/12/3748
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