Popular GitHub Repositories for Agriculture Knowledgegraph

FarmVibes.AI: Multi-Modal GeoSpatial ML Models for Agriculture and Sustainability

USING BERT FOR Attribute Extraction in KnowledgeGraph. fine-tuning and feature extraction. 使用基于bert的微调和特征提取方法来进行知识图谱百度百科人物词条属性抽取。

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.

Software for self driving lawn tractor.

Building and Using Knowledge Graphs made easy

? This project aims to automate plant health monitoring using computer vision and deep learning. It focuses on accurate disease detection and classification in plants through rigorous data preprocessing and robust model selection.

https://soilnet.herokuapp.com/ Created a Soil Classification model using Deep Learning which also suggests Crops in 6 different languages and deployed on Heroku. Soil Classification is one of the most important topics, for Farmers and Agriculture Researchers.

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

Android app for plant disease identification using ML

智能农业咨询系统是一款应用程序，旨在为农民提供个性化的作物管理、病虫害防治和灌溉安排建议。该系统利用机器学习模型，分析各种环境和土壤参数，推荐最适合种植的作物。

Source codes for groundwater pumping prediction using integrated remote sensing datasets and machine learning

[ECCV 2024 Workshop?] The first agriculture benchmark to evaluate MM-LLMs.

EuroCropsML is a ready-to-use benchmark dataset for few-shot crop type classification using Sentinel-2 imagery.

This is a LLM model, where it is tuned to help the farmers for clarifying their doubts about organic farming, with personalised suggestions.

A Convolutional Neural Network approach for image-based anomaly detection in smart agriculture

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.

Harness the power of machine learning to forecast rice and wheat crop yields per acre in India, aiming to empower smallholder farmers, combat poverty and malnutrition, utilizing data from Digital Green surveys to revolutionize agriculture and promote sustainable practices in the face of climate change for enhanced global food security.

AI to Predict Yield in Aeroponics

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

Revolutionize your farming with Farmwiser, the ultimate TinyML based Smart Agriculture solution!