Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 1100767

Use of Convolutional Neural Network for Fish Species Classification


(VSB Techial University of Ostrava) Štifanić, Daniel; Musulin, Jelena; Car, Zlatan; Čep, Robert;
Use of Convolutional Neural Network for Fish Species Classification // Pomorski zbornik, 59 (2020), 1; 131-142 doi:18048/2020.59.08. (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1100767 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Use of Convolutional Neural Network for Fish Species Classification

Autori
Štifanić, Daniel ; Musulin, Jelena ; Car, Zlatan ; Čep, Robert ;

Kolaboracija
VSB Techial University of Ostrava

Izvornik
Pomorski zbornik (0554-6397) 59 (2020), 1; 131-142

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Machine learning ; convolutional neural network ; fish species classification ; underwater video

Sažetak
Fish population monitoring systems based on underwater video recording are becoming more popular nowadays, however, manual processing and analysis of such data can be time- consuming. Therefore, by utilizing machine learning algorithms, the data can be processed more efficiently. In this research, authors investigate the possibility of convolutional neural network (CNN) implementation for fish species classification. The dataset used in this research consists of four fish species (Plectroglyphidodon dickii, Chromis chrysura, Amphiprion clarkii, and Chaetodon lunulatus), which gives a total of 12859 fish images. For the aforementioned classification algorithm, different combinations of hyperparameters were examined as well as the impact of different activation functions on the classification performance. As a result, the best CNN classification performance was achieved when Identity activation function is applied to hidden layers, RMSprop is used as a solver with a learning rate of 0.001, and a learning rate decay of 1e-5. Accordingly, the proposed CNN model is capable of performing high-quality fish species classifications.

Izvorni jezik
Engleski

Znanstvena područja
Interdisciplinarne tehničke znanosti



POVEZANOST RADA


Projekti:
Ostalo-CEI - 305.6019-20 - USE OF REGRESSIVE ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML) METHODS IN MODELLING OF COVID-19 SPREAD – COVIDAI (COVIDAi) (Car, Zlatan, Ostalo - CEI Extraordinary Call for Proposals 2020) ( POIROT)
EK-EFRR-KK.01.2.2.03 - Centar kompetencija za pametne gradove (CEKOM) (Car, Zlatan, EK - Podrška razvoju Centara kompetencija, Europski Fond za Regionalni Razvoj / Support to the development of Competence Centers, European Regional Development Fund KK.01.2.2.03.) ( POIROT)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-275-1447 - Razvoj inteligentnog ekspertnog sustava za online diagnostiku raka mokračnog mjehura (Car, Zlatan, NadSve - UNIRI potpore) ( POIROT)
InoUstZnVO-CIII-HR-0108-10 - Concurrent Product and Technology Development - Teaching, Research and Implementation of Joint Programs Oriented in Production and Industrial Engineering (Car, Zlatan, InoUstZnVO - CEEPUS) ( POIROT)
EK-KF-KK.01.1.1.01.0009-1 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima - IJ za znanost o podatcima (Lončarić, Sven, EK - KK.01.1.1.01) ( POIROT)
EK-KF-KK.01.1.1.01.009 - DATACROSS - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (DATACROSS) (Lončarić, Sven; Ivan, Petrović, EK ) ( POIROT)

Ustanove:
Tehnički fakultet, Rijeka

Profili:

Avatar Url Zlatan Car (autor)

Citiraj ovu publikaciju

(VSB Techial University of Ostrava) Štifanić, Daniel; Musulin, Jelena; Car, Zlatan; Čep, Robert;
Use of Convolutional Neural Network for Fish Species Classification // Pomorski zbornik, 59 (2020), 1; 131-142 doi:18048/2020.59.08. (međunarodna recenzija, članak, znanstveni)
(VSB Techial University of Ostrava) (VSB Techial University of Ostrava) Štifanić, D., Musulin, J., Car, Z., Čep, R. & (2020) Use of Convolutional Neural Network for Fish Species Classification. Pomorski zbornik, 59 (1), 131-142 doi:18048/2020.59.08..
@article{article, year = {2020}, pages = {131-142}, DOI = {18048/2020.59.08.}, keywords = {Machine learning, convolutional neural network, fish species classification, underwater video}, journal = {Pomorski zbornik}, doi = {18048/2020.59.08.}, volume = {59}, number = {1}, issn = {0554-6397}, title = {Use of Convolutional Neural Network for Fish Species Classification}, keyword = {Machine learning, convolutional neural network, fish species classification, underwater video} }
@article{article, year = {2020}, pages = {131-142}, DOI = {18048/2020.59.08.}, keywords = {Machine learning, convolutional neural network, fish species classification, underwater video}, journal = {Pomorski zbornik}, doi = {18048/2020.59.08.}, volume = {59}, number = {1}, issn = {0554-6397}, title = {Use of Convolutional Neural Network for Fish Species Classification}, keyword = {Machine learning, convolutional neural network, fish species classification, underwater video} }

Citati





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font