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Based on my published research paper, this project uses a "One-vs-All" deep learning approach with EfficientNet B4 to classify cassava leaf diseases. Integrated into an Android app, it helps farmers detect diseases early, supporting sustainable farming and reducing crop losses.
🚀 Mobile-first plant disease detection using CoreML & CreateML An iOS app that leverages computer vision to classify plant diseases in real-time. Trained on 87k+ images, the model achieves good accuracy and works offline, making it ideal for farmers and agronomists in remote areas.
🌿 AgroMind - AI-Driven Plant Health Advisor A smart Flutter app that helps home gardeners detect plant diseases, receive AI-driven care tips, and engage in a community for plant enthusiasts.
A Python-based Streamlit application backed by a custom database of 44 official Integrated Pest Management (IPM) guides, designed to help farmers identify and manage crop pests.
Flutter mobile application for 18-channel spectroscopy. It uses Bluetooth Low Energy (BLE) to communicate with a Raspberry Pi Pico 2W connected to an AS7265x spectral sensor
A Machine Learning project for Plant Disease Prediction using Random Forest, Streamlit, and Google Colab. Includes interactive UI and detailed analysis.