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

Microbiome analysis for phosphate-defense interaction

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

Zhian Kamvar's Ph. D. dissertation from Oregon State University

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

Analysis of Plant Pathogen Pathotype Complexities, Distributions and Diversity

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

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

Classifier build to recognize disease on apple leaves images

Population genetic analysis of _Phytophthora ramorum_ data from Oregon forests in Curry County

Use of computational vision techniques to detect plant diseases

Contains my kaggle kernels

Seminar delivered at the University of Aberystwyth, 19th June 2017

Este es un espacio de un no-programador para no-programadores que quieren aprender un poco más de sobre ciencia de datos, genética y bioinformática. Y porque no, un lugar en donde los programadores pueden colaborarnos en este proyecto.