DeFungi
Donated on 1/28/2023
DeFungi is a dataset for direct mycological examination of microscopic fungi images. The images are from superficial fungal infections caused by yeasts, moulds, or dermatophyte fungi. The images have been manually labelled into five classes and curated with a subject matter expert assistance. The images have been cropped with automated algorithms to produce the final dataset.
Dataset Characteristics
Image
Subject Area
Computer Science
Associated Tasks
Classification
Feature Type
Real
# Instances
9114
# Features
-
Dataset Information
For what purpose was the dataset created?
The dataset was created to develop a machine-learning algorithm for detecting and classifying Fungi images.
Who funded the creation of the dataset?
No funder.
What do the instances in this dataset represent?
Photos
Are there recommended data splits?
No
Does the dataset contain data that might be considered sensitive in any way?
No
Was there any data preprocessing performed?
Yes. The dataset has been pre-processed. All images have been cropped to the region of interest.
Has Missing Values?
No
Introductory Paper
By C. Sopo, Farshid Hajati, S. Gheisari. 2021
Published in Medical Mycology
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset defungi = fetch_ucirepo(id=773) # data (as pandas dataframes) X = defungi.data.features y = defungi.data.targets # metadata print(defungi.metadata) # variable information print(defungi.variables)
Hajati,Farshid, Javier Pineda Sopo,Camilo, Hajati,Farshid, and Gheisari,Soheila. (2023). DeFungi. UCI Machine Learning Repository. https://doi.org/10.48550/arXiv.2109.07322.
@misc{misc_defungi_773,
author = {Hajati,Farshid, Javier Pineda Sopo,Camilo, Hajati,Farshid, and Gheisari,Soheila},
title = {{DeFungi}},
year = {2023},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.48550/arXiv.2109.07322}
}Keywords
Creators
Farshid Hajati
hajati@gmail.com
Camilo Javier Pineda Sopo
camilo.pinedasopo@live.vu.edu.au
Victoria University
Farshid Hajati
farshid.hajati@vu.edu.au
Victoria University
Soheila Gheisari
soheila.gheisari@vu.edu.au
Victoria University
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.