Zur Kurzanzeige

dc.contributor.authorNiebling, Florian
dc.contributor.authorHaas, Michael
dc.contributor.authorBlessing, Andre´
dc.contributor.editorDraude, Claude
dc.contributor.editorLange, Martin
dc.contributor.editorSick, Bernhard
dc.date.accessioned2019-08-27T13:00:16Z
dc.date.available2019-08-27T13:00:16Z
dc.date.issued2019
dc.identifier.isbn978-3-88579-689-3
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/25049
dc.description.abstractThis paper presents a case study of integrating RESTful web services for software development in the Digital Humanities. Journalists today are able to utilize huge amounts of image data to illustrate their articles. To provide easy access, image databases need to be structured and photographic documents stored within need to be categorized. Here, methods based on Deep Learning have recently had a significant impact on image categorization. We highlight the potentials of incorporating machine learning with different models for named-entity recognition in image captions, to facilitate classification of images according to standard IPTC media topics. We finally discuss the results of our project employing service-oriented architectures integrating specialized components to simplify the creation of DH applications.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft (Workshop-Beiträge)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-295
dc.subjectService-oriented Architecture
dc.subjectDigital Humanities
dc.subjectClassification of Images
dc.subjectMachine Learning
dc.titleIntegration of Services for Software Development in DH: A Case Study of Image Classification using Convolutional Neural Networksen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages163-168
mci.conference.sessiontitleSoftware Engineering in den Digital Humanities
mci.conference.locationKassel
mci.conference.date23.-26. September 2019
dc.identifier.doi10.18420/inf2019_ws17


Dateien zu dieser Ressource

Thumbnail

Zur Kurzanzeige