The rapidly evolving field of artificial intelligence (AI) continues to witness the introduction of
innovative open-source pre-trained models, fostering advancements in various applications …

Diabetic Retinopathy is one of the leading global causes of vision impairment and blindness
in humans. It has seen a rise in prevalence, necessitating the development of advanced …

Progress in medical imaging models using supervised learning has reached closer to
clinical-level performance of doctors. However, labeling huge amounts of medical data …

Diabetic retinopathy (DR) is a diabetic condition that affects vision, despite the great success
of supervised learning and Conventional Neural Networks (CNNs), it's still challenging to …

Diabetic Retinopathy (DR) evaluations are increasingly being automated using artificial
intelligence. Diabetes-related retinal vascular disease is a major cause of blindness and …

Diabetes retinopathy (DR) is the primary cause of blindness worldwide. Computer-aided
diagnosis methods for early detection of DR fundus images are time and effort-saving and …

The Industrial Internet of Things (IIoT) integrates interconnected sensors and devices to
support industrial applications, but its dynamic environments pose challenges related to …

The early detection of Diabetic Retinopathy (DR) is necessary to aid doctors in treating
retina patient to increase their existence rate. Due to the major imbalance dataset issue in …

Deep learning approaches have attracted a lot of attention as a way to classify retinal fundus
images that include diabetic retinopathy (DR) because the old method of manual detection …

Diabetes Retinopathy, a leading cause of vision impairment, necessitates early and precise
detection. To address this, we developed a Convolutional Neural Network (CNN) model and …