Diagnosis of Diabetic Retinopathy through Retinal Fundus Images and 3D Convolutional Neural Networks with Limited Number of Samples
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Title
Diagnosis of Diabetic Retinopathy through Retinal Fundus Images and 3D Convolutional Neural Networks with Limited Number of Samples
Authors
Keywords
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Journal
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
Volume 2021, Issue -, Pages 1-15
Publisher
Hindawi Limited
Online
2021-11-18
DOI
10.1155/2021/6013448
References
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- (2021) Shunpu Tang et al. Physical Communication
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- (2021) Abd Ullah Khan et al. IEEE Wireless Communications Letters
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- (2021) Wali Ullah Khan et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
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- Automated Detection and Classification of Fundus Diabetic Retinopathy Images using Synergic Deep Learning Model
- (2020) Shankar Kathiresan et al. PATTERN RECOGNITION LETTERS
- Deep and Densely Connected Networks for Classification of Diabetic Retinopathy
- (2020) Hamza Riaz et al. Diagnostics
- SMO-DNN: Spider Monkey Optimization and Deep Neural Network Hybrid Classifier Model for Intrusion Detection
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- Comparison of smartphone-based retinal imaging systems for diabetic retinopathy detection using deep learning
- (2020) Mahmut Karakaya et al. BMC BIOINFORMATICS
- Deep learning algorithms for detection of diabetic retinopathy in retinal fundus photographs: A systematic review and meta-analysis
- (2020) Md Mohaimenul Islam et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Automated detection of diabetic retinopathy using convolutional neural networks on a small dataset
- (2020) Abhishek Samanta et al. PATTERN RECOGNITION LETTERS
- A Note on Implementation Methodologies of Deep Learning-Based Signal Detection for Conventional MIMO Transmitters
- (2020) Junjuan Xia et al. IEEE TRANSACTIONS ON BROADCASTING
- Global, regional, and national burden and trend of diabetes in 195 countries and territories: an analysis from 1990 to 2025
- (2020) Xiling Lin et al. Scientific Reports
- Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders
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- (2020) Ke He et al. Physical Communication
- Efficient Power-Splitting and Resource Allocation for Cellular V2X Communications
- (2020) Furqan Jameel et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Modified Alexnet architecture for classification of diabetic retinopathy images
- (2019) T. Shanthi et al. COMPUTERS & ELECTRICAL ENGINEERING
- Secure Cache-Aided Multi-Relay Networks in the Presence of Multiple Eavesdroppers
- (2019) Junjuan Xia et al. IEEE TRANSACTIONS ON COMMUNICATIONS
- Diabetic retinopathy detection using red lesion localization and convolutional neural networks
- (2019) Gabriel Tozatto Zago et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Domain Progressive 3D Residual Convolution Network to Improve Low-Dose CT Imaging
- (2019) Xiangrui Yin et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Early detection of diabetic retinopathy
- (2018) Hamid Safi et al. SURVEY OF OPHTHALMOLOGY
- Structurally-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising
- (2018) Chenyu You et al. IEEE Access
- Deep convolutional neural networks for diabetic retinopathy detection by image classification
- (2018) Shaohua Wan et al. COMPUTERS & ELECTRICAL ENGINEERING
- Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy
- (2018) Rory Sayres et al. OPHTHALMOLOGY
- Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database
- (2017) Joon Yul Choi et al. PLoS One
- Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
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- Computer-aided diagnosis of diabetic retinopathy: A review
- (2013) Muthu Rama Krishnan Mookiah et al. COMPUTERS IN BIOLOGY AND MEDICINE
- TeleOphta: Machine learning and image processing methods for teleophthalmology
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- (2012) Shuiwang Ji et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
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