Detection of trees on street-view images using a convolutional neural network

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.creatorJodas, Danilo Samuel-
Autor(es): dc.creatorYojo, Takashi-
Autor(es): dc.creatorBrazolin, Sergio-
Autor(es): dc.creatorDel Nero Velasco, Giuliana-
Autor(es): dc.creatorPapa, João Paulo-
Data de aceite: dc.date.accessioned2025-08-21T22:07:04Z-
Data de disponibilização: dc.date.available2025-08-21T22:07:04Z-
Data de envio: dc.date.issued2022-05-01-
Data de envio: dc.date.issued2022-05-01-
Data de envio: dc.date.issued2020-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1142/S0129065721500428-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/233506-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/233506-
Descrição: dc.descriptionReal-time detection of possible deforestation of urban landscapes is an essential task for many urban forest monitoring services. Computational methods emerge as a rapid and efficient solution to evaluate bird's-eye-view images taken by satellites, drones, or even street-view photos captured at the ground level of the urban scenery. Identifying unhealthy trees requires detecting the tree itself and its constituent parts to evaluate certain aspects that may indicate unhealthiness, being street-level images a cost-effective and feasible resource to support the fieldwork survey. This paper proposes detecting trees and their specific parts on street-view images through a Convolutional Neural Network model based on the well-known You Only Look Once network with a MobileNet as the backbone for feature extraction. Essentially, from a photo taken from the ground, the proposed method identifies trees, isolates them through their bounding boxes, identifies the crown and stem, and then estimates the height of the trees by using a specific handheld object as a reference in the images. Experiment results demonstrate the effectiveness of the proposed method.-
Descrição: dc.descriptionDepartment of Computing São Paulo State University-
Descrição: dc.descriptionInstitute for Technological Research University of São Paulo-
Descrição: dc.descriptionDepartment of Computing São Paulo State University-
Idioma: dc.languageen-
Relação: dc.relationInternational Journal of Neural Systems-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectMachine learning-
Palavras-chave: dc.subjectSmart cities-
Palavras-chave: dc.subjectSustainability-
Palavras-chave: dc.subjectUrban forest-
Título: dc.titleDetection of trees on street-view images using a convolutional neural network-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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