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
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