Diabetic Retinopathy Detection using Deep Learning Methodology-Reference-Cited by-同舟云学术

Diabetic Retinopathy Detection using Deep Learning Methodology

Published:2022-10-07 Issue: Volume: Page:
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Container-title:2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)
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Author:

Kumar Arsha V¹,Babu Anoop S¹

Affiliation:

1. Amrita Vishwa Vidyapeetham,Department of Computer Science and Engineering,Amritapuri,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9971791/9971808/09971891.pdf?arnumber=9971891

Reference33 articles.

1. A Topological-Attention ConvLSTM Network and Its Application to EM Images

2. Combining LSTM and DenseNet for Automatic Annotation and Classification of Chest X-Ray Images

3. Classification of diabetic retinopathy through identification of diagnostic keywords;yadeeswaran;2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA),2021

4. Attention‐based spatial–temporal hierarchical ConvLSTM network for action recognition in videos

5. Pair wise training for stacked convolutional autoencoders using small scale images

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1. A Hybrid Diabetic Retinopathy Neural Network Model for Early Diabetic Retinopathy Detection and Classification of Fundus Images;Traitement du Signal;2023-12-30

2. Exploring the Potential of EfficientNetB7 for Diabetic Retinopathy Classification: A Comprehensive Analysis;2023 5th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N);2023-12-15

3. An Ensemble Deep Learning Model for Diabetic Retinopathy Identification;2023 9th International Conference on Smart Structures and Systems (ICSSS);2023-11-23