CDAM-Net: Channel shuffle dual attention based multi-scale CNN for efficient glaucoma detection using fundus images

Author:

Das Dipankar,Nayak Deepak RanjanORCID,Bhandary Sulatha V.,Acharya U. Rajendra

Funder

Department of Science and Technology, Ministry of Science and Technology, India

Science and Engineering Research Board

Publisher

Elsevier BV

Reference60 articles.

1. Automated diagnosis of glaucoma using texture and higher order spectra features;Acharya;IEEE Trans. Inf. Technol. Biomed.,2011

2. Decision support system for the glaucoma using Gabor transformation;Acharya;Biomed. Signal Process. Control,2015

3. Automated glaucoma detection using quasi-bivariate variational mode decomposition from fundus images;Agrawal;IET Image Process.,2019

4. Efficient detection of glaucoma using double tier deep convolutional neural network;Babu;Pers. Ubiquitous Comput.,2022

5. Interleaved deep artifacts-aware attention mechanism for concrete structural defect classification;Bhattacharya;IEEE Trans. Image Process.,2021

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