Brazilian Agricultural Research Corporation (EMBRAPA) fully annotated dataset for plant diseases. Plug and play installation over PiP.
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Updated
Mar 22, 2019 - Python
Brazilian Agricultural Research Corporation (EMBRAPA) fully annotated dataset for plant diseases. Plug and play installation over PiP.
Various Kaggle image classification challenges solutions
A systematic/quantitative review of articles, which provides a basis for identifying what has been done so far in the field of plant pathology research reproducibility and suggestions for ways to improving it.
AI-powered plant disease detection system using deep learning. Upload plant images to instantly identify 30+ diseases across Apple, Corn, Grape, Potato, Tomato & more crops. Built with FastAPI + React TypeScript. Ready for cloud deployment.
Analysis for "Population structure and phenotypic variation of *Sclerotinia sclerotiorum* from dry bean (*Phaseolus vulgaris*) in the United States"
This project is an AI-powered plant disease prediction tool utilizing Convolutional Neural Networks (CNN). It is specialized for identifying diseases in maize, potato, tomato, and rice crops, helping farmers and agricultural professionals detect and manage crop diseases early.
Analysis of various Deep Learning architectures for the detection of Corn🌽 Leaf Diseases
Raspberry Pi Grow Box Control Software
Microbiome analysis for phosphate-defense interaction
🌿 AI-powered plant disease detection system using MobileNetV2 transfer learning. Detects 38 plant diseases across 14 crops with 98.55% accuracy. Built with TensorFlow, Keras, and Streamlit. Includes trained model, sample dataset, and web interface.
Leaf disc scoring pipeline for estimating the area of infection on leaf discs from inoculation experiments.
Solution IA dédiée à la surveillance des cultures tropicales, permettant la détection automatique de la mosaïque du manioc et des dégâts causés par la chenille légionnaire d'automne sur le maïs grâce à la vision par ordinateur et à YOLOv11. — https://huggingface.co/kjd-dktech/agbledo01
NuKropAI 🌾🤖 — Production-Ready Agriculture Intelligence
Systematic optimization of MobileNetV2 for citrus plant disease detection. Includes 18+ detailed experiments on hyperparameters, augmentations, and fine-tuning. Part of the Agro-AI project for Teknofest 2026.
Medico is an AI model which assess the health of an apple leaf and classifies to one of the four categories
Zhian Kamvar's Ph. D. dissertation from Oregon State University
AI-powered plant disease detection web app. Upload leaf photos for real-time diagnosis using GPT-4 Vision or Claude 3 Opus. Get detailed reports with severity, symptoms, treatment, and prevention. Built with React, FastAPI, and Tailwind CSS.
Agricultural pathology classification and microclimate risk forecasting engine powered by PyTorch vision models, leaf image diagnostics, and treatment recommendations.
Android app for estimating apple tree condition
Kaggle's plant disease image classification competition. Finetuning pre-trained CNN models, loss functions, and optimizers in order to achieve better results.
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