Project / 03

AI-Powered Ocular Disease Detection

A CNN-based image classification system for detecting ocular diseases using image preprocessing and data augmentation.

Category

AI / ML · Computer Vision

Key Result

94% Accuracy

01Overview

The project

A deep learning-based computer vision project focused on detecting multiple ocular diseases from medical images. The system uses image preprocessing, data augmentation and a convolutional neural network for classification.

02Architecture

System architecture

Medical Image

Preprocessing

Data Augmentation

CNN

Classification

03Model Evaluation

Model performance

ACCURACY

94%

Overall classification accuracy achieved by the CNN model.

SENSITIVITY

92%

Sensitivity achieved during model evaluation.

SPECIFICITY

93%

Specificity achieved during model evaluation.

04Results

Measured performance.

94%

Accuracy

92%

Sensitivity

93%

Specificity

05Technology
PythonTensorFlowOpenCVNumPyCNN