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.

Analysis for "Population structure and phenotypic variation of *Sclerotinia sclerotiorum* from dry bean (*Phaseolus vulgaris*) in the United States"

Raspberry Pi Grow Box Control Software

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.

The Cotton Disease Detection System is an AI-powered web application that helps farmers and agricultural experts identify diseases in cotton plants through image analysis.

Microbiome analysis for phosphate-defense interaction

Analysis of various Deep Learning architectures for the detection of Corn🌽 Leaf Diseases

Leaf disc scoring pipeline for estimating the area of infection on leaf discs from inoculation experiments.

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

Kaggle's plant disease image classification competition. Finetuning pre-trained CNN models, loss functions, and optimizers in order to achieve better results.

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.

Use of computational vision techniques to detect plant diseases

Contains my kaggle kernels

Identificação de doenças em folhas de maçã, utilizando rede neural convolucional. Identificando as folhas que estão saudáveis, as que estão infectadas com a ferrugem da macieira, as que têm sarna da macieira e as que têm mais de uma doença.

Analysis of Plant Pathogen Pathotype Complexities, Distributions and Diversity

I am a Senior Research Scientist at CSIRO who specialises in Agroecological modelling.

Presentation delivered at the 2017 EUPHRESCO workshop in Edinburgh, 1st November 2017