A fish detection approach based on BAT algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86099050" target="_blank" >RIV/61989100:27240/16:86099050 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-26690-9_25" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-26690-9_25</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-26690-9_25" target="_blank" >10.1007/978-3-319-26690-9_25</a>

Result language
angličtina
Original language name
A fish detection approach based on BAT algorithm
Original language description
Fish detection and identification are important steps towards monitoring fish behavior. The importance of such monitoring step comes from the need for better understanding of the fish ecology and issuing conservative actions for keeping the safety of this vital food resource. The recent advances in machine learning approaches allow many applications to easily analyze and detect a number of fish species. The main competence between these approaches is based on two main detection parameters: the time and the accuracy measurements. Therefore, this paper proposes a fish detection approach based on BAT optimization algorithm (BA). This approach aims to reduce the classification time within the fish detection process. The performance of this system was evaluated by a number of well-known machine learning classifiers, KNN, ANN, and SVM. The approach was tested with 151 images to detect the Nile Tilapia fish species and the results showed that k-NN can achieve high accuracy 90 %, with feature reduction ratio close to 61 % along with a noticeable decrease in the classification time. (C) Springer International Publishing Switzerland 2016.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Advances in Intelligent Systems and Computing. Volume 407
ISBN
978-3-319-26688-6
ISSN
2194-5357
e-ISSN
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Number of pages
11
Pages from-to
273-283
Publisher name
Springer Verlag
Place of publication
London
Event location
Beni Suef
Event date
Nov 28, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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