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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Detection of Trees on Street-View Images Using a Convolutional Neural Network

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Jodas, Danilo Samuel [1, 2] ; Yojo, Takashi [2] ; Brazolin, Sergio [2] ; Velasco, Giuliana Del Nero [2] ; Papa, Joao Paulo [1]
Total Authors: 5
[1] Sao Paulo State Univ, Dept Comp, BR-17033360 Bauru, SP - Brazil
[2] Univ Sao Paulo, Inst Technol Res, BR-05508901 Sao Paulo, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: International Journal of Neural Systems; v. 32, n. 01 JAN 2022.
Web of Science Citations: 0

Real-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. (AU)

FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:Alexandre Xavier Falcão
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
Grantee:Fabio Gagliardi Cozman
Support Opportunities: Research Grants - Research Centers in Engineering Program
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:José Alberto Cuminato
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 17/50343-2 - Institutional development plan in the area of digital transformation: advanced manufacturing and smart and sustainable cities (PDIp)
Grantee:Zehbour Panossian
Support Opportunities: Research Grants - State Research Institutes Modernization Program
FAPESP's process: 19/18287-0 - Real-time Urban Forest Management Using Machine Learning
Grantee:Danilo Samuel Jodas
Support Opportunities: Scholarships in Brazil - Post-Doctorate