There are 0 repository under plant-pathology topic.
Various Kaggle image classification challenges solutions
Brazilian Agricultural Research Corporation (EMBRAPA) fully annotated dataset for plant diseases. Plug and play installation over PiP.
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"
Analysis of various Deep Learning architectures for the detection of Corn🌽 Leaf Diseases
Medico is an AI model which assess the health of an apple leaf and classifies to one of the four categories
Leaf disc scoring pipeline for estimating the area of infection on leaf discs from inoculation experiments.
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.
Analysis of Plant Pathogen Pathotype Complexities, Distributions and Diversity
Classifier build to recognize disease on apple leaves images
Population genetic analysis of _Phytophthora ramorum_ data from Oregon forests in Curry County
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.
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.
Use of computational vision techniques to detect plant diseases
Android app for estimating apple tree condition
Seminar delivered at the University of Aberystwyth, 19th June 2017
Presentation delivered at the 2017 EUPHRESCO workshop in Edinburgh, 1st November 2017