Convolutional Neural Networks for Diabetic Retinopathy

Convolutional Neural Networks for Diabetic Retinopathy The diagnosis of diabetic retinopathy (DR) through colour fundus images requires experienced clinicians to identify the presenceĀ and significance of many small features which, along with a complex grading system, makes this a dicult and time consuming task. In this paper, we propose a CNN approach to diagnosing DR from digital fundus images and accurately classifying its severity. We develop a network with CNN architecture and data augmentation which can identify the intricate features involved in the classification task such as micro-aneurysms, exudate and haemorrhages…

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Face detection and recognition and attendance using machine learning and deep learning

This project is proposed for real time face detection and recognition. The project is implemented in both machine learning and deep learning. Implementation step: Face is detected in real time, detected face is trained with atleast 1000 frames for good accuracy. The training the collected data Face recognition with input and mark attendance Software used: Python Python Project Demo

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