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A hybrid dual-stream CNN framework with dynamic data augmentation and improved Manta Ray Foraging Optimization for robust glaucoma detection.

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第一作者： Azza,Atia

第一单位： Department of Information Systems, Faculty of Computers and Information, Kafrelsheikh University, Kafrelsheikh, Egypt. azzamohamed@fci.kfs.edu.eg.

作者： Azza,Atia ^[1] ; Hatem,Abdel-Kader ^[2] ; Osama M,Abo-Seida ^[3] ; Amira,Abdelatey ^[4]

作者单位： Department of Information Systems, Faculty of Computers and Information, Kafrelsheikh University, Kafrelsheikh, Egypt. azzamohamed@fci.kfs.edu.eg. ^[1] Department of Information Systems, Faculty of Computers and Information, Menoufia University, Shibin El-Kom, Al Minufiyah, Egypt. ^[2] Department of Computer Science, Faculty of Computers and Information, Kafrelsheikh University, Kafrelsheikh, Egypt. ^[3] Department of Information Systems, Faculty of Computers and Information, Menoufia University, Shibin El-Kom, Al Minufiyah, Egypt.;Faculty of Computers and Artificial Intelligence, Menoufia National University, Tukh Tambisha, Al Minufiyah, Egypt. ^[4]

关键词 Dual-stream convolutional neural network (CNN)Dynamic Gaussian noise Glaucoma detection Lightweight channel-wise attention mechanism

医学主题词青光眼(Glaucoma);人类(Humans);算法(Algorithms);图像处理, 计算机辅助(Image Processing, Computer-Assisted)

DOI 10.1038/s41598-026-45384-6

PMID 41998000

发布时间 2026-05-08

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准确一般字义偏差语意偏离译文作用小提交