Identification of Cichlid Fishes from Lake Malawi Using Computer Vision

Deokjin Joo; Ye-seul Kwan; Jongwoo Song; Catarina Pinho; Jody Hey; Yong-Jin Won

doi:10.1371/journal.pone.0077686

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Open Access

Peer-reviewed

Research Article

Identification of Cichlid Fishes from Lake Malawi Using Computer Vision

Deokjin Joo,

Affiliation Department of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea
⨯
Ye-seul Kwan,

Affiliation Division of EcoScience, Ewha Womans University, Seoul, Korea
⨯
Jongwoo Song,

Affiliation Department of Statistics, Ewha Womans University, Seoul, Korea
⨯
Catarina Pinho,

Affiliation CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Vairão, Portugal
⨯
Jody Hey,

Affiliation Department of Biology, Temple University, Philadelphia, Pennsylvania, United States of America
⨯
Yong-Jin Won

* E-mail: won@ewha.ac.kr

Affiliation Division of EcoScience, Ewha Womans University, Seoul, Korea
⨯

Identification of Cichlid Fishes from Lake Malawi Using Computer Vision

Deokjin Joo,
Ye-seul Kwan,
Jongwoo Song,
Catarina Pinho,
Jody Hey,
Yong-Jin Won

Published: October 25, 2013
https://doi.org/10.1371/journal.pone.0077686

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A deep learning implementation is available, as a tutorial code

Posted by jdjzdz on 29 Oct 2021 at 13:10 GMT

The average accuracy with deep learning techniques is 0.8254 ± 0.0423 and F1-score is 0.770435 ± 0.059, with 10 randomized trials. In our 2013 work, the accuracies were 0.6649 and 0.7562 for 48-feature-classifier and 82-feature-classifier, respectively.

The repository is here: https://github.com/forcec...

We also made the dataset available.

No competing interests declared.

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Identification of Cichlid Fishes from Lake Malawi Using Computer Vision

Identification of Cichlid Fishes from Lake Malawi Using Computer Vision

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A deep learning implementation is available, as a tutorial code

Posted by jdjzdz on 29 Oct 2021 at 13:10 GMT