PlantAi is a ResNet-based CNN model trained on the PlantVillage dataset to classify plant leaf images as healthy or diseased. This repository includes PyTorch training code, tools to convert the model to TensorFlow Lite (TFLite) for deployment, and an Android app integrating the model for real-time leaf disease detection from camera images.

MangoMediX 🌿 – AI-powered mango leaf disease prediction system using ResNet50, Flask, and a user-friendly web interface. Detects 8 mango leaf diseases with 92% accuracy and provides treatment suggestions.

Data augmentation framework and convolutional neural network for classification of cassava crop diseases from leaf images 🌱

GreenFund is an AI-powered web application that empowers farmers to make data-driven, climate-smart agricultural decisions. The platform focuses on analysis of soil health then additionally tracks farm activities, measures carbon emissions, and provides AI-driven crop recommendations to promote sustainable and climate-resilient farming.

Deep Learning Project for Sugarcane Disease Prediction and Classification Using CNN Architectures

Hyperparameter-tuned Xception model for plant disease detection with 97.23% accuracy – published at IEEE ICAIQSA 2024

Cocoa Plant Detection + GIS AI Pipeline | YOLOv8 + QGIS + Streamlit

A Django-based AI-powered system for classifying banana ripeness from images and providing value addition suggestions. The project integrates a trained machine learning model for ripeness detection, a backend API, and a frontend interface for users.

A Deep Learning Architecture to detect if a lemon tree is diseased or healthy by looking at an image of its leaf

PyTorch deep learning model for potato disease classification. Implements custom CNN and transfer learning (ResNet50, EfficientNet-B0) to identify Early Blight, Late Blight, and healthy potato leaves with 95%+ accuracy.

AI-powered web application for real-time plant leaf disease detection using a fine-tuned ResNet-34 CNN, built with PyTorch and Flask.

🚀 A scalable Python backend for an AI chatbot built for agriculture and aquaculture. It delivers real-time insights on crops, pest detection, and fish farming. With secure APIs and modular design, it integrates seamlessly into apps, empowering farmers 🌱 and businesses to boost productivity, efficiency, and sustainability.

🌱 AI-powered crop disease detection app for farmers. Identify plant diseases, get treatment recommendations, and connect with the farming community using React Native.

Deep learning model for detecting plant diseases using CNN and Streamlit.

RootSource | BlueDot | Bangladesh | "Revolutionizing Agriculture Through Artificial Intelligence"

The AI Spray Coverage Tracker is an AI-powered agricultural tool that analyzes spray photos to measure droplet coverage and optimize pesticide efficiency. Built with HTML, Vue.js, JavaScript, and jsPDF, it helps farmers reduce chemical waste, improve crop protection, and generate professional PDF/CSV reports — fully compatible with WordPress

A Computer Vision application using Transfer Learning (MobileNetV2) to classify the age and health of Bambusa wamin and perform digital morphometric measurements using reference object calibration.

A professional, AI-powered tool that helps farmers predict future cattle market prices, calculate break-even points, and plan optimal selling times. Built with HTML, PHP, JS, Vue.js, and Python — fully compatible with WordPress Elementor. Export PDF and CSV reports directly from the browser.

Repository containing codes, figures, and supplementary materials for the journal article “Deep Learning-Based Models for Paddy Disease Classification and Segmentation: An Experimental Review.”

AI-powered plant health diagnostic app with image analysis, weather, soil data integration. Multi-language support, real-time monitoring. Built with React, TypeScript, Vite.