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Pregled bibliografske jedinice broj: 1093691

Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis


Lorencin, Ivan; Anđelić, Nikola; Baressi Šegota, Sandi; Musulin, Jelena; Štifanić, Daniel; Mrzljak, Vedran; Španjol, Josip; Car, Zlatan
Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis // Studies in Computational Intelligence "Enabling AI Applications in Data Science" / Hassanien, Aboul-Ella ; N. Taha, Mohamed Hamed ; M. Khalifa, Nour Eldeen (ur.).
Cham: Springer, 2021. str. 225-245 doi:10.1007/978-3-030-52067-0_10


CROSBI ID: 1093691 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis
(Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis)

Autori
Lorencin, Ivan ; Anđelić, Nikola ; Baressi Šegota, Sandi ; Musulin, Jelena ; Štifanić, Daniel ; Mrzljak, Vedran ; Španjol, Josip ; Car, Zlatan

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Studies in Computational Intelligence "Enabling AI Applications in Data Science"

Urednik/ci
Hassanien, Aboul-Ella ; N. Taha, Mohamed Hamed ; M. Khalifa, Nour Eldeen

Izdavač
Springer

Grad
Cham

Godina
2021

Raspon stranica
225-245

ISBN
978-3-030-52067-0

ISSN
1860-949X

Ključne riječi
Edge Detector ; Artificial Neural Network ; Urinary Bladder Cancer

Sažetak
A standard procedure of ANN utilization in tasks of image recognition and classification includes use of convolutional neural networks (CNN). Such procedure represents a standard approach with applications in various fields of science and technology. Described trend can also be noticed in medical applications. Such approach can be costly from a standpoint of computational resources. For these reasons, the utilization of simpler algorithms can be of significant importance. This feature is particularly emphasized in clinical practice where fewer computing resources are available. Here lies a motive for utilization of hybrid ANN models. In this chapter, an idea of edge detector-based ANN models utilization in diagnosis of urinary bladder cancer is presented.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne medicinske znanosti, Kliničke medicinske 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.01.2.2.03.0004 - Centar kompetencija za pametne gradove (CEKOM) (Car, Zlatan; Slavić, Nataša, EK - 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)
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)
KK.01.1.1.01.0009 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima (EK )

Ustanove:
Medicinski fakultet, Rijeka,
Tehnički fakultet, Rijeka,
Klinički bolnički centar Rijeka

Profili:

Avatar Url Josip Španjol (autor)

Avatar Url Zlatan Car (autor)

Avatar Url Vedran Mrzljak (autor)

Avatar Url Nikola Anđelić (autor)

Avatar Url Ivan Lorencin (autor)

Citiraj ovu publikaciju

Lorencin, Ivan; Anđelić, Nikola; Baressi Šegota, Sandi; Musulin, Jelena; Štifanić, Daniel; Mrzljak, Vedran; Španjol, Josip; Car, Zlatan
Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis // Studies in Computational Intelligence "Enabling AI Applications in Data Science" / Hassanien, Aboul-Ella ; N. Taha, Mohamed Hamed ; M. Khalifa, Nour Eldeen (ur.).
Cham: Springer, 2021. str. 225-245 doi:10.1007/978-3-030-52067-0_10
Lorencin, I., Anđelić, N., Baressi Šegota, S., Musulin, J., Štifanić, D., Mrzljak, V., Španjol, J. & Car, Z. (2021) Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis. U: Hassanien, A., N. Taha, M. & M. Khalifa, N. (ur.) Studies in Computational Intelligence "Enabling AI Applications in Data Science". Cham, Springer, str. 225-245 doi:10.1007/978-3-030-52067-0_10.
@inbook{inbook, year = {2021}, pages = {225-245}, DOI = {10.1007/978-3-030-52067-0\_10}, keywords = {Edge Detector, Artificial Neural Network, Urinary Bladder Cancer}, doi = {10.1007/978-3-030-52067-0\_10}, isbn = {978-3-030-52067-0}, issn = {1860-949X}, title = {Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis}, keyword = {Edge Detector, Artificial Neural Network, Urinary Bladder Cancer}, publisher = {Springer}, publisherplace = {Cham} }
@inbook{inbook, year = {2021}, pages = {225-245}, DOI = {10.1007/978-3-030-52067-0\_10}, keywords = {Edge Detector, Artificial Neural Network, Urinary Bladder Cancer}, doi = {10.1007/978-3-030-52067-0\_10}, isbn = {978-3-030-52067-0}, issn = {1860-949X}, title = {Edge Detector-Based Hybrid Artificial Neural Network Models for Urinary Bladder Cancer Diagnosis}, keyword = {Edge Detector, Artificial Neural Network, Urinary Bladder Cancer}, publisher = {Springer}, publisherplace = {Cham} }

Časopis indeksira:


  • Scopus


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