D

Deep Learning

AgriGuard AI is an AI-powered, offline crop disease detection and agricultural advisory system that uses computer vision and deep learning to identify crop diseases from images, estimate disease severity, and provide treatment and prevention recommendations. Designed for farmers and agricultural professionals, the system operates without an internet connection, ensuring reliable field deployment in remote areas while promoting sustainable and precision agriculture

The primary objective is to develop machine learning models capable of assisting in early detection and accurate diagnosis of these conditions based on patient data.

TruthLens is an AI-powered misinformation detection tool that analyzes text, audio, and video to identify and flag potentially misleading content.

OCU-AI is a smart healthcare assistant that combines Natural Language Processing (NLP) and Computer Vision to assist users in understanding medical conditions and detecting eye diseases from retinal images.

This web-based application has two core components:

Medical Q&A Chatbot

Uses Retrieval-Augmented Generation (RAG) with LangChain, Pinecone, and Phi-3 LLM.

Answers user queries using embedded medical knowledge extracted from PDF files (like textbooks or research).

Designed to explain medical terms in simple, non-technical language.

Always includes a disclaimer to consult a qualified medical professional.

Eye Disease Detection Model

Allows users to upload retina images.

Predicts diseases like:

Cataract

Glaucoma

Diabetic Retinopathy

Normal (Healthy)

Uses a Keras CNN model trained on retina datasets.

After prediction, the chatbot explains the condition using natural language.

This project bridges AI-powered document retrieval, medical imaging, and LLM-based explanation, offering a foundation for real-world smart health applications.