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Pregled bibliografske jedinice broj: 1159218

Ultrasound Anomaly Detection Based on Variational Autoencoders

Milković, Fran; Filipović, Branimir; Subašić, Marko; Petković, Tomislav; Lončarić, Sven; Budimir, Marko
Ultrasound Anomaly Detection Based on Variational Autoencoders // 2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA)
Zagreb, Hrvatska: Institute of Electrical and Electronics Engineers (IEEE), 2021. str. 225-229 doi:10.1109/ISPA52656.2021.9552041 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)

CROSBI ID: 1159218 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Ultrasound Anomaly Detection Based on Variational Autoencoders

Autori
Milković, Fran ; Filipović, Branimir ; Subašić, Marko ; Petković, Tomislav ; Lončarić, Sven ; Budimir, Marko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) / - : Institute of Electrical and Electronics Engineers (IEEE), 2021, 225-229

Skup
12th International Symposium on Image and Signal Processing and Analysis (ISPA 2021)

Mjesto i datum
Zagreb, Hrvatska, 13.09.2021. - 15.09.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
ultrasonic testing , anomaly detection , variational autoencoder , deep learning , computer vision

Sažetak
Analysis of ultrasonic testing (UT) data is a time-consuming assignment. In order to make it less demanding we propose an approach based on a variational autoencoder (VAE) to filter out the scans without anomalies/defects and in doing so, partially automate the procedure. The implemented approach uses an additional encoder network allowing to encode the reconstructed images. The differences in encodings of input and reconstructed images have shown to be good indicators of anomalous data. Anomaly detection results surpass the results of other VAE based anomaly criteria.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Interdisciplinarne tehničke znanosti



POVEZANOST RADA

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Tomislav Petković (autor)

Avatar Url Marko Subašić (autor)

Avatar Url Branimir Filipović (autor)

Avatar Url Marko Budimir (autor)

Avatar Url Sven Lončarić (autor)

Avatar Url Fran Milković (autor)

Poveznice na cjeloviti tekst rada:

doi doi.org ieeexplore.ieee.org

Citiraj ovu publikaciju:

Milković, Fran; Filipović, Branimir; Subašić, Marko; Petković, Tomislav; Lončarić, Sven; Budimir, Marko
Ultrasound Anomaly Detection Based on Variational Autoencoders // 2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA)
Zagreb, Hrvatska: Institute of Electrical and Electronics Engineers (IEEE), 2021. str. 225-229 doi:10.1109/ISPA52656.2021.9552041 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Milković, F., Filipović, B., Subašić, M., Petković, T., Lončarić, S. & Budimir, M. (2021) Ultrasound Anomaly Detection Based on Variational Autoencoders. U: 2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) doi:10.1109/ISPA52656.2021.9552041.
@article{article, author = {Milkovi\'{c}, Fran and Filipovi\'{c}, Branimir and Suba\v{s}i\'{c}, Marko and Petkovi\'{c}, Tomislav and Lon\v{c}ari\'{c}, Sven and Budimir, Marko}, year = {2021}, pages = {225-229}, DOI = {10.1109/ISPA52656.2021.9552041}, keywords = {ultrasonic testing , anomaly detection , variational autoencoder , deep learning , computer vision}, doi = {10.1109/ISPA52656.2021.9552041}, title = {Ultrasound Anomaly Detection Based on Variational Autoencoders}, keyword = {ultrasonic testing , anomaly detection , variational autoencoder , deep learning , computer vision}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, publisherplace = {Zagreb, Hrvatska} }
@article{article, author = {Milkovi\'{c}, Fran and Filipovi\'{c}, Branimir and Suba\v{s}i\'{c}, Marko and Petkovi\'{c}, Tomislav and Lon\v{c}ari\'{c}, Sven and Budimir, Marko}, year = {2021}, pages = {225-229}, DOI = {10.1109/ISPA52656.2021.9552041}, keywords = {ultrasonic testing , anomaly detection , variational autoencoder , deep learning , computer vision}, doi = {10.1109/ISPA52656.2021.9552041}, title = {Ultrasound Anomaly Detection Based on Variational Autoencoders}, keyword = {ultrasonic testing , anomaly detection , variational autoencoder , deep learning , computer vision}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, publisherplace = {Zagreb, Hrvatska} }

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