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Reusability in Artificial Neural Networks: An Empirical Study

dc.contributor.authorGhofrani, Javad
dc.contributor.authorKozegar, Ehsan
dc.contributor.authorBozorgmehr, Arezoo
dc.contributor.authorSoorati, Mohammad Divband
dc.contributor.editorFelderer, Michael
dc.contributor.editorHasselbring, Wilhelm
dc.contributor.editorRabiser, Rick
dc.contributor.editorJung, Reiner
dc.date.accessioned2020-02-03T13:03:56Z
dc.date.available2020-02-03T13:03:56Z
dc.date.issued2020
dc.identifier.isbn978-3-88579-694-7
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/31751
dc.description.abstractThis manuscript summarizes our empirical study on reuse in the context of Artificial Neural Networks (ANNs) extensively described in [Gh19b] as a paper with the same title, presented in 2nd International Workshop on Experiences and Empirical Studies on Software Reuse (WEESR 2019)en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftware Engineering 2020
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-300
dc.subjectSoftware Development
dc.subjectSoftware Process
dc.subjectHybrid Methods
dc.subjectSurvey Research
dc.titleReusability in Artificial Neural Networks: An Empirical Studyen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages37--38
mci.conference.sessiontitleDomänen-spezifische Softwareentwicklung
mci.conference.locationInnsbruck, Austria
mci.conference.date24.-28. Feburar 2020
dc.identifier.doi10.18420/SE2020_07


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