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Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches
Deep learning-based medical image analysis has shown strong potential in disease
categorization, segmentation, detection, and even prediction. However, in high-stakes and …
categorization, segmentation, detection, and even prediction. However, in high-stakes and …
An ensemble approach to detect diabetic retinopathy using the residual contrast limited adaptable histogram equalization method
S Shilpa, B Karthik - 2023 Second International Conference on …, 2023 - ieeexplore.ieee.org
If untreated, diabetic retinopathy (DR), an irreversible disease of the retina brought on by
high blood sugar, can cause blindness. In this research, a unique automated method for DR …
high blood sugar, can cause blindness. In this research, a unique automated method for DR …
Challenges and solutions with lightweight models for diabetic retinopathy detection
Diabetes retinopathy (DR) will become the primary cause of blindness in develo** nations
if it is not properly managed at the appropriate time. A cost-effective method for screening a …
if it is not properly managed at the appropriate time. A cost-effective method for screening a …
Deep Learning-Based Multi-class Classification of Diabetic Retinopathy Utilizing Transfer Learning with MobileNet Architecture
This study examined the performance characteristics of several architectures to establish the
finest model for DR diagnosis. After evaluating alternative architectures, the MobileNet …
finest model for DR diagnosis. After evaluating alternative architectures, the MobileNet …
Ensemble Deep Learning for DR Identification: Integrating DenseNet121 and VGG19 Architectures
Diabetic retinopathy (DR) is a severe complication of diabetes affecting the retina, potentially
leading to vision impairment or blindness. Deep learning for diabetic retinopathy …
leading to vision impairment or blindness. Deep learning for diabetic retinopathy …