Synergy of Convolutional Neural Networks and Geometric Active Contours

Uproszczony widok
dc.contributor.authorTomczyk, Arkadiusz
dc.contributor.authorPankiv, Oleksandr
dc.contributor.authorSzczepaniak, Piotr S.
dc.date.accessioned2021-10-25T10:08:19Z
dc.date.available2021-10-25T10:08:19Z
dc.date.issued2021
dc.description.abstractHybrid approach to machine learning techniques could potentially provide improvements in image segmentation results. In this paper, a model of cooperation of convolutional neural networks and geometric active contours is proposed and developed. The novelty of the approach lies in combining deep neural networks and active contour model in order to improve CNN output results. The method is examined on the image segmentation task and applied to the detection and extraction of nuclei of HL60 cell line. The model had been tested on both 2-D and 3-D images. Because of feature learning characteristics of convolutional neural networks, the proposed solution should perform well in multiple scenarios and can be considered generic.en_EN
dc.identifier.citationTomaczyk A., Pankiv O., Szczepaniak Piotr S., Synergy of Convolutional Neural Networks and Geometric Active Contours. W: TEWI 2021 (Technology, Education, Knowledge, Innovation),Wojciechowski A. (Ed.), Napieralski P. (Ed.), Lipiński P. (Ed.)., Seria: Monografie PŁ;Nr 2378, Wydawnictwo Politechniki Łódzkiej, Łódź 2021, s. 207-215, ISBN 978-83-66741-10-2, DOI 10.34658/9788366741102.14.
dc.identifier.doi10.34658/9788366741102.14
dc.identifier.isbn978-83-66741-10-2
dc.identifier.urihttp://hdl.handle.net/11652/4030
dc.identifier.urihttps://doi.org/10.34658/9788366741102.14
dc.language.isoenen_EN
dc.page.numbers. 207-215
dc.publisherWydawnictwo Politechniki Łódzkiejpl_PL
dc.publisherLodz University of Technology Pressen_EN
dc.relation.ispartofWojciechowski A. (Ed.), Napieralski P. (Ed.), Lipiński P. (Ed.)., TEWI 2021 (Technology, Education, Knowledge, Innovation), Seria: Monografie PŁ;Nr 2378, Wydawnictwo Politechniki Łódzkiej, Łódź 2021, ISBN 978-83-66741-10-2, DOI 10.34658/9788366741102.
dc.relation.ispartofseriesMonografie Politechniki Łódzkiej; 2378pl_PL
dc.relation.ispartofseriesLodz University of Technology Monographs; 2378en_EN
dc.rightsFair use conditionen_EN
dc.rightsDla wszystkich w zakresie dozwolonego użytkupl_PL
dc.rights.licenseLUT Licenseen_EN
dc.rights.licenseLicencja PŁpl_PL
dc.subjectconvolutional neural networksen_EN
dc.subjectCNNen_EN
dc.subjectgeometric active contoursen_EN
dc.subjectGACen_EN
dc.subjectimage segmentationen_EN
dc.subjectbiomedical applicationsen_EN
dc.subjectmachine learningen_EN
dc.subjectsplotowe sieci neuronowepl_PL
dc.subjectgeometryczne aktywne konturypl_PL
dc.subjectsegmentacja obrazupl_PL
dc.subjectzastosowania biomedycznepl_PL
dc.subjectuczenie maszynowepl_PL
dc.titleSynergy of Convolutional Neural Networks and Geometric Active Contoursen_EN
dc.typeRozdział książkipl_PL
dc.typeBook chapteren_EN

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