MicrAnt: Towards Regression Task Oriented Annotation Tool for Microscopic Image

dc.contributor.authorJiřík, Miroslav
dc.contributor.authorMoulisová, Vladimíra
dc.contributor.authorSchindler, Claudia
dc.contributor.authorČervenková, Lenka
dc.contributor.authorPálek, Richard
dc.contributor.authorRosendorf, Jáchym
dc.contributor.authorArlt, Janine
dc.contributor.authorBolek, Lukáš
dc.contributor.authorDejmek, Jiří
dc.contributor.authorDahmen, Uta
dc.contributor.authorJiříková, Kamila
dc.contributor.authorGruber, Ivan
dc.contributor.authorLiška, Václav
dc.contributor.authorŽelezný, Miloš
dc.date.accessioned2021-03-15T11:00:28Z
dc.date.available2021-03-15T11:00:28Z
dc.date.issued2020
dc.description.abstract-translatedAnnotating a dataset for training a Supervised Machine Learning algorithm is time and annotator’s attention intensive. Our goal was to create a tool that would enable us to create annotations of the dataset with minimal demands on expert’s time. Inspired by applications such as Tinder, we have created an annotation tool for describing microscopic images. A graphical user interface is used to select from a couple of images the one with the higher value of the examined parameter. Two experiments were performed. The first compares the speed of annotation of our application with the commonly used tool for processing microscopic images. In the second experiment, the texture description was compared with the annotations from MicrAnt application and commonly used application. The results showed that the processing time using our application is 3 times lower and the Spearman coefficient increases by 0.05 than using a commonly used application. In an experiment, we have shown that the annotations processed using our application increase the correlation of the studied parameter and texture descriptors compared with manual annotations.en
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationJIŘÍK, M. MOULISOVÁ, V. SCHINDLER, C. ČERVENKOVÁ, L. PÁLEK, R. ROSENDORF, J. ARLT, J. BOLEK, L. DEJMEK, J. DAHMEN, U. JIŘÍKOVÁ, K. GRUBER, I. LIŠKA, V. ŽELEZNÝ, M.MicrAnt: Towards Regression Task Oriented Annotation Tool for Microscopic Image. In: Combinatorial Image Analysis 20th International Workshop, IWCIA 2020, Novi Sad, Serbia, July 16–18, 2020, Proceedings. Cham: Springer, 2020. s. 209-218. ISBN 978-3-030-51001-5, ISSN 0302-9743.cs
dc.identifier.doi10.1007/978-3-030-51002-2_15
dc.identifier.isbn978-3-030-51001-5
dc.identifier.issn0302-9743
dc.identifier.obd43930832
dc.identifier.uri2-s2.0-85088565236
dc.identifier.urihttp://hdl.handle.net/11025/42935
dc.language.isoenen
dc.project.IDLO1506/PUNTIS - Podpora udržitelnosti centra NTIS - Nové technologie pro informační společnostcs
dc.publisherSpringeren
dc.relation.ispartofseriesCombinatorial Image Analysis 20th International Workshop, IWCIA 2020, Novi Sad, Serbia, July 16–18, 2020, Proceedingsen
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights© Springeren
dc.rights.accessrestrictedAccessen
dc.subject.translatedmicroscopyen
dc.subject.translatedannotationen
dc.subject.translatedscaffolden
dc.subject.translatedliveren
dc.subject.translateddecellularizationen
dc.titleMicrAnt: Towards Regression Task Oriented Annotation Tool for Microscopic Imageen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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