Innovative infrastructure to access Brazilian fungal diversity using deep learning

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dc.creatorThiago Chaves
dc.creatorElisandro Ricardo Drechsler-Santos
dc.creatorJoicymara Santos Xavier
dc.creatorAlfeu Gonçalves dos Santos
dc.creatorKelmer Martins-Cunha
dc.creatorFernanda Karstedt
dc.creatorThiago Kossmann
dc.creatorSusanne Sourell
dc.creatorEloisa Leopoldo
dc.creatorMiriam Nathalie Fortuna Ferreira
dc.creatorRoger Farias
dc.creatorMahatmã Titton
dc.creatorGenivaldo Alves-Silva
dc.creatorFelipe Bittencourt
dc.creatorDener Bortolini
dc.creatorEmerson L. Gumboski
dc.creatorAldo von Wangenheim
dc.creatorAristóteles Góes-Neto
dc.date.accessioned2026-01-06T21:35:03Z
dc.date.issued2024
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
dc.description.sponsorshipOutra Agência
dc.identifier.doihttps://doi.org/10.7717/peerj.17686
dc.identifier.issn2167-8359
dc.identifier.urihttps://hdl.handle.net/1843/1306
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofPeerJ: life & environment
dc.rightsAcesso aberto
dc.subjectBiodiversidade
dc.subjectBiologia Computacional
dc.subjectMicologia
dc.subjectAprendizagem Profunda
dc.subjectFungos
dc.titleInnovative infrastructure to access Brazilian fungal diversity using deep learning
dc.typeArtigo de periódico
local.citation.epage23
local.citation.spage1
local.description.resumoIn the present investigation, we employ a novel and meticulously structured database assembled by experts, encompassing macrofungi field-collected in Brazil, featuring upwards of 13,894 photographs representing 505 distinct species. The purpose of utilizing this database is twofold: firstly, to furnish training and validation for convolutional neural networks (CNNs) with the capacity for autonomous identification of macrofungal species; secondly, to develop a sophisticated mobile application replete with an advanced user interface. This interface is specifically crafted to acquire images, and, utilizing the image recognition capabilities afforded by the trained CNN, proffer potential identifications for the macrofungal species depicted therein. Such technological advancements democratize access to the Brazilian Funga, thereby enhancing public engagement and knowledge dissemination, and also facilitating contributions from the populace to the expanding body of knowledge concerning the conservation of macrofungal species of Brazil.
local.publisher.countryBrasil
local.publisher.departmentICB - DEPARTAMENTO DE MICROBIOLOGIA
local.publisher.initialsUFMG
local.subject.cnpqCIENCIAS BIOLOGICAS
local.url.externahttps://peerj.com/articles/17686/

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