A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

Taufik Budhi Pramono; R. Ardharyan Islamy; Saprudin; Joni Johanda Putra; Teddy Suparyanto; Kartika Purwandari; Tjeng Wawan Cenggoro; Bens Pardamean

doi:10.1088/1755-1315/794/1/012114

A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

Taufik Budhi Pramono
, R. Ardharyan Islamy
, Saprudin
, Joni Johanda Putra
, Teddy Suparyanto
, Kartika Purwandari^*
, Tjeng Wawan Cenggoro
, Bens Pardamean

^*Corresponding author for this work

Faculty of Fisheries and Marine Sciences

Research output: Contribution to journal › Conference article › peer-review

11 Citations (Scopus)

Abstract

Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.

Original language	English
Article number	012114
Journal	IOP Conference Series: Earth and Environmental Science
Volume	794
Issue number	1
DOIs	https://doi.org/10.1088/1755-1315/794/1/012114
Publication status	Published - 2 Aug 2021
Event	4th International Conference on Eco Engineering Development 2020, ICEED 2020 - Banten, Indonesia Duration: 10 Nov 2020 → 11 Nov 2020

Keywords

deep learning
fish image classification
intelligent system
siluformes

Access to Document

10.1088/1755-1315/794/1/012114

Cite this

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title = "A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order",

abstract = "Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89\% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.",

keywords = "deep learning, fish image classification, intelligent system, siluformes",

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doi = "10.1088/1755-1315/794/1/012114",

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T1 - A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

AU - Pramono, Taufik Budhi

AU - Islamy, R. Ardharyan

AU - Saprudin,

AU - Putra, Joni Johanda

AU - Suparyanto, Teddy

AU - Purwandari, Kartika

AU - Cenggoro, Tjeng Wawan

AU - Pardamean, Bens

N1 - Publisher Copyright: © Published under licence by IOP Publishing Ltd.

PY - 2021/8/2

Y1 - 2021/8/2

N2 - Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.

AB - Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.

KW - deep learning

KW - fish image classification

KW - intelligent system

KW - siluformes

UR - https://www.scopus.com/pages/publications/85112576998

U2 - 10.1088/1755-1315/794/1/012114

DO - 10.1088/1755-1315/794/1/012114

M3 - Conference article

AN - SCOPUS:85112576998

SN - 1755-1307

VL - 794

JO - IOP Conference Series: Earth and Environmental Science

JF - IOP Conference Series: Earth and Environmental Science

IS - 1

M1 - 012114

T2 - 4th International Conference on Eco Engineering Development 2020, ICEED 2020

Y2 - 10 November 2020 through 11 November 2020

ER -

A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

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Keywords

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