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Methods for Automatic Image-Based Classification of Winged Insects Using Computational Techniques: A Systematic Literature Review

Authors:

Allan Rodrigues Rebelo,

Joao Marcos Garcia Fagundes,

Luciano Antonio Digiampietri,

Helton Hideraldo BíscaroAuthors Info & Claims

SBSI '20: Proceedings of the XVI Brazilian Symposium on Information Systems

Article No.: 31, Pages 1 - 8

https://doi.org/10.1145/3411564.3411641

Published: 03 November 2020 Publication History

Abstract

Artificial intelligence has been used in conjunction with computational and statistical techniques for automatic identification of insect species because of the current growing demand for this type of solution. This study presents the results of a Systematic Literature Review conducted to evaluate the state of the art of automatic image-based classification methods of winged insects. One thousand and sixty studies were researched and thirty-six were fully analyzed, and, from the results obtained, it was concluded that the area is consolidating with an uptrend and that there are techniques with satisfactory results for the proposed objectives, but there are still major problems to be solved.

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Cited By

Mestetskiy LGuru DBenifa JNagendraswamy HChola C(2022)Gender identification of Drosophila melanogaster based on morphological analysis of microscopic imagesThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-022-02447-939:5(1815-1827)Online publication date: 19-Mar-2022
https://dl.acm.org/doi/10.1007/s00371-022-02447-9
Rebelo AFagundes JDigiampietri LFrancoy TBíscaro H(2021)A fully automatic classification of bee species from wing imagesApidologie10.1007/s13592-021-00887-152:6(1060-1074)Online publication date: 22-Oct-2021
https://doi.org/10.1007/s13592-021-00887-1

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SBSI '20: Proceedings of the XVI Brazilian Symposium on Information Systems

November 2020

371 pages

ISBN:9781450388733

DOI:10.1145/3411564

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 03 November 2020

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SBSI'20: XVI Brazilian Symposium on Information Systems

November 3 - 6, 2020

São Bernardo do Campo, Brazil

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Cited By

Mestetskiy LGuru DBenifa JNagendraswamy HChola C(2022)Gender identification of Drosophila melanogaster based on morphological analysis of microscopic imagesThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-022-02447-939:5(1815-1827)Online publication date: 19-Mar-2022
https://dl.acm.org/doi/10.1007/s00371-022-02447-9
Rebelo AFagundes JDigiampietri LFrancoy TBíscaro H(2021)A fully automatic classification of bee species from wing imagesApidologie10.1007/s13592-021-00887-152:6(1060-1074)Online publication date: 22-Oct-2021
https://doi.org/10.1007/s13592-021-00887-1

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