Published Paper Details:

Cataract, a common eye condition characterized by clouding of the lens, remains a leading cause of vision impairment worldwide. Timely detection and intervention are crucial for effective management of this condition. In this project, we propose a novel approach for cataract detection leveraging deep learning methods techniques.In this project, we introduce a novel method for detecting cataracts using deep learning. We utilize the EfficientNetB0 model for its efficiency and robustness in image classification tasks and implement parallel processing with a ThreadPoolExecutor to optimize computational resources. Using the ODIR-5K dataset, we train and evaluate the model, achieving an impressive 96.80 % accuracy in cataract detection. Our results demonstrate the model's efficacy in distinguishing between normal and cataractous retinal images, offering a promising solution for early detection and intervention in cataract-related visual impairments.