Popular GitHub Repositories for Agricultural

AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.

Open Source Deep Learning Serving System with Web Interface

COMPAG 2025: Adaptive LiDAR-only Odometry and Mapping Framework in Agricultural Environments

Research and Development of Agricultural Large Models|农业大模型研究与开发

A system that is capable of automatically irrigating the agricultural field by sensing the parameters of soil in real-time and predicting crop based on those parameters using machine learning. The system also predicts the yield of the crop.

This Chatbot helps farmers make informed decisions by leveraging the power of LLM Model from OpenAI.

AgriGenius: AI-Powered Agriculture Chatbot is a Python web application designed to empower farmers with information accessibility. AgriGenius leverages a Retrieval-Augmented Generation model to address farmer's agricultural queries with precise answers.

Helping Farmers make informed decisions with Machine Learning ! ?‍??

Detecting and segmenting destructive anomalies in farmland from satellite images, improving time, efficiency, and crop yield.

Image recognition for corn leaf disease. The model has been deployed as an android application for easy use by farmers and agricultural professionals.

Multiagent Pathfinding Problem for agricultural swarm agents. Used CBS algorithm for search. To know more, refer to the report attached in the link below.

This project leverages LSTM networks, a type of RNN, to accurately predict fruit and vegetable prices by analyzing a comprehensive dataset, utilizing a refined model adept at navigating the complexities and patterns within agricultural market data.

This project provides an API for uploading PDF documents and extracting structured summaries using either OpenAI's GPT-4o or Anthropic's Claude models. It is optimized for environmental and agricultural reports, transforming unstructured PDF content into structured JSON for downstream use.

Agmar LSTM Model is a project that implements a Long Short-Term Memory (LSTM) model to predict the modal price of agricultural commodities. The model utilizes historical data to forecast future prices, aiding in decision-making for farmers and traders.

A curated list of high-quality resources, tools, platforms, and research related to agricultural drones (UAVs) for precision farming and crop management.

FarmFlow is an AI-powered advisory platform designed to assist rice farmers in optimizing their agricultural practices. By combining expert farming knowledge with real-time insights, FarmFlow provides personalized recommendations on crop health, resource use, and cost-saving strategies.

Developed an android mobile app (GreenFinder), trained, and evaluated two deep learning image classification models for the use-case. The mobile app classifies scanned fruits, vegetables and flowers, as well as provides knowledgeable information on each classified item.

Agri Chatbot is an interactive application designed to assist users with agricultural queries and to enable easy access to the latest research for everyone.

This project provides a valuable tool for farmers, enabling them to manage rice plant diseases effectively and improve crop yield. The combination of advanced deep learning techniques and mobile technology offers a practical solution for real-world agricultural challenges.

Algorithm developed to assist in the navigation of autonomous agricultural machines.