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<div><p>In this paper, a novel hybrid network called ChessFormer is proposed for the single image de-rain task. The network seamlessly integrates the advantages of Transformer and fitted neural network (CNN) in a checkerboard architecture, fully utilizing the global modeling capability o...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Yutian Yang (14572502) (author)
مؤلفون آخرون:	Jianyu Lin (13512940) (author), Xinyue Dai (738111) (author), Zhipei Zhang (334287) (author), Shuijin Zhang (21377442) (author), Yingyu Chen (161120) (author), Guangxin Kong (21377445) (author), Xin Li (51274) (author)
منشور في:	2025
الموضوعات:	Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Physical Sciences not elsewhere classified Information Systems not elsewhere classified single image de multiple benchmark datasets multilevel feature extraction mechanism image textures global modeling capability gated phase operation features across dimensions experimental results show network seamlessly integrates fitted neural network different rain patterns multidimensional transposed attention network fusion rain task rain line xlink "> visual quality quantitative metrics msta ), fully utilizing efficiently achieve combining self chessformer adopts checkerboard architecture art performance achieving state
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