Ritiksb007/Major_Project
This project uses MobileNetV2 to detect Diabetic Retinopathy (DR) and classify its severity. It supports binary (DR vs. No DR) and multiclass (Mild, Moderate, Proliferative_DR, Severe) classifications. Deployed on Hugging Face, it enables efficient and accessible DR detection for healthcare applications.
No commits in the last 6 months.
Stars
3
Forks
1
Language
Jupyter Notebook
License
—
Category
Last pushed
Dec 14, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Ritiksb007/Major_Project"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
rsk97/Diabetic-Retinopathy-Detection
DIAGNOSIS OF DIABETIC RETINOPATHY FROM FUNDUS IMAGES USING SVM, KNN, and attention-based CNN...
cauchyturing/kaggle_diabetic_RAM
Extended Retinopathy Detection Challenge with the Regression Activation Map for visual explaination
javathunderman/diabetic-retinopathy-screening
Diabetic retinopathy screening w/ Tensorflow.
JordiCorbilla/ocular-disease-intelligent-recognition-deep-learning
ODIR-2019: Ocular Disease Intelligent Recognition is a project leveraging state-of-the-art deep...
koriavinash1/Optic-Disk-Cup-Segmentation
Optic Disc and Optic Cup Segmentation using 57 layered deep convolutional neural network