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Publication details

Document type
Journal articles

Document subtype
Full paper

Title
BivalveNet: A hybrid deep neural network for common cockle (Cerastoderma edule) geographical traceability based on shell image analysis

Participants in the publication
Ronnie Concepcion (Author)
Marielet Guillermo (Author)
Susanne E. Tanner (Author)
Dep. Biologia Animal
 MARE
 Vanessa Fonseca (Author)
Dep. Biologia Animal
 MARE
 Bernardo Duarte (Author)
Dep. Biologia Vegetal
 MARE
Date of Publication
2023-10

Where published
Ecological Informatics

Publication Identifiers
ISSN - 1574-9541

Publisher
Elsevier BV

Starting page
102344

Document Identifiers
DOI - https://doi.org/10.1016/j.ecoinf.2023.102344
URL - http://dx.doi.org/10.1016/j.ecoinf.2023.102344

Rankings
SCOPUS Q1 (2021) - 5.4 - Ecology


Export

APA
Ronnie Concepcion, Marielet Guillermo, Susanne E. Tanner, Vanessa Fonseca, Bernardo Duarte, (2023). BivalveNet: A hybrid deep neural network for common cockle (Cerastoderma edule) geographical traceability based on shell image analysis. Ecological Informatics, ISSN 1574-9541. eISSN . http://dx.doi.org/10.1016/j.ecoinf.2023.102344

IEEE
Ronnie Concepcion, Marielet Guillermo, Susanne E. Tanner, Vanessa Fonseca, Bernardo Duarte, "BivalveNet: A hybrid deep neural network for common cockle (Cerastoderma edule) geographical traceability based on shell image analysis" in Ecological Informatics, 2023. 10.1016/j.ecoinf.2023.102344

BIBTEX
@article{59553, author = {Ronnie Concepcion and Marielet Guillermo and Susanne E. Tanner and Vanessa Fonseca and Bernardo Duarte}, title = {BivalveNet: A hybrid deep neural network for common cockle (Cerastoderma edule) geographical traceability based on shell image analysis}, journal = {Ecological Informatics}, year = 2023, }