Don’t Tear Your Hair Out: Analysis of the Impact of Skin Hair on the Diagnosis of Microscopic Skin Lesions

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

Recent work on the classification of microscopic skin lesions does not consider how the presence of skin hair may affect diagnosis. In this work, we investigate how deep-learning models can handle a varying amount of skin hair during their predictions. We present an automated processing pipeline that tests the performance of the classification model. We conclude that, under realistic conditions, modern day classification models are robust to the presence of skin hair and we investigate three architectural choices (Resnet50, InceptionV3, Densenet121) that make them so.

Originele taal-2Engels
TitelPattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings
RedacteurenAlberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani
UitgeverijSpringer
Pagina's406-416
Aantal pagina's11
ISBN van geprinte versie9783030687625
DOI's
StatusGepubliceerd - 2021
Evenement25th International Conference on Pattern Recognition Workshops, ICPR 2020 - Milan, Italië
Duur: 10 jan 202115 jan 2021
Congresnummer: 25
https://www.micc.unifi.it/icpr2020/

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12661 LNCS
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Congres

Congres25th International Conference on Pattern Recognition Workshops, ICPR 2020
Verkorte titelICPR 2020
Land/RegioItalië
StadMilan
Periode10/01/2115/01/21
Internet adres

Bibliografische nota

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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