Website for online plant diseases analysis from images with advanced search engine.
A lung disease classification app: React frontend, Flask backend, and a DenseNet121 model trained to 94.8% accuracy on chest X-rays.
Medical AI platform for Diabetic Retinopathy detection & grading (ICDR scale) via CNN ensembles (DenseNet169, ResNet50, EfficientNet). FastAPI, PyTorch, React.
A Web Application that predicts the presence of Pneumonia from X-Ray Images using a DenseNet Neural Network model. Tech Stack: React as frontend , Python Flask as backend and Mongo DB.
This project is a simple web application for image classification built using Django and PyTorch. It uses a pretrained DenseNet model to classify uploaded images based on ImageNet labels.
Detect abnormalities in chest X-rays using a DenseNet121 classifier trained on the NIH ChestX-ray14 dataset, served via FastAPI with Grad-CAM explainability and a React frontend.
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