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Digital Classification of Chilean Pelagic Species in Fishing Landing Lines.
Caro Fuentes, Vincenzo; Torres, Ariel; Luarte, Danny; Pezoa, Jorge E; Godoy, Sebastián E; Torres, Sergio N; Urbina, Mauricio A.
Afiliação
  • Caro Fuentes V; Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Concepción, Concepción 4070371, Chile.
  • Torres A; Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Concepción, Concepción 4070371, Chile.
  • Luarte D; Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Concepción, Concepción 4070371, Chile.
  • Pezoa JE; Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Concepción, Concepción 4070371, Chile.
  • Godoy SE; Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Concepción, Concepción 4070371, Chile.
  • Torres SN; Departamento de Ingeniería Eléctrica, Facultad de Ingeniería, Universidad de Concepción, Concepción 4070371, Chile.
  • Urbina MA; Departamento de Zoología, Facultad de Ciencias Naturales y Oceanográficas, Universidad de Concepción, Concepción 4070386, Chile.
Sensors (Basel) ; 23(19)2023 Sep 29.
Article em En | MEDLINE | ID: mdl-37836993
Fishing landings in Chile are inspected to control fisheries that are subject to catch quotas. The control process is not easy since the volumes extracted are large and the numbers of landings and artisan shipowners are high. Moreover, the number of inspectors is limited, and a non-automated method is utilized that normally requires months of training. In this work, we propose, design, and implement an automated fish landing control system. The system consists of a custom gate with a camera array and controlled illumination that performs automatic video acquisition once the fish landing starts. The imagery is sent to the cloud in real time and processed by a custom-designed detection algorithm based on deep convolutional networks. The detection algorithm identifies and classifies different pelagic species in real time, and it has been tuned to identify the specific species found in landings of two fishing industries in the Biobío region in Chile. A web-based industrial software was also developed to display a list of fish detections, record relevant statistical summaries, and create landing reports in a user interface. All the records are stored in the cloud for future analyses and possible Chilean government audits. The system can automatically, remotely, and continuously identify and classify the following species: anchovy, jack mackerel, jumbo squid, mackerel, sardine, and snoek, considerably outperforming the current manual procedure.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Conservação dos Recursos Naturais / Caça Limite: Animals País/Região como assunto: America do sul / Chile Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Chile País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Conservação dos Recursos Naturais / Caça Limite: Animals País/Região como assunto: America do sul / Chile Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Chile País de publicação: Suíça