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Image-based Decision Support Systems: Technical Concepts, Design Knowledge, and Applications for Sustainability

Walk, Jannis 1,2
1 Karlsruhe Service Research Institute (KSRI), Karlsruher Institut für Technologie (KIT)
2 Institut für Wirtschaftsinformatik und Marketing (IISM), Karlsruher Institut für Technologie (KIT)

Abstract (englisch):

Unstructured data accounts for 80-90% of all data generated, with image data contributing its largest portion. In recent years, the field of computer vision, fueled by deep learning techniques, has made significant advances in exploiting this data to generate value. However, often computer vision models are not sufficient for value creation. In these cases, image-based decision support systems (IB-DSSs), i.e., decision support systems that rely on images and computer vision, can be used to create value by combining human and artificial intelligence. Despite its potential, there is only little work on IB-DSSs so far.
In this thesis, we develop technical foundations and design knowledge for IBDSSs and demonstrate the possible positive effect of IB-DSSs on environmental sustainability. The theoretical contributions of this work are based on and evaluated in a series of artifacts in practical use cases: First, we use technical experiments to demonstrate the feasibility of innovative approaches to exploit images for IBDSSs.
We show the feasibility of deep-learning-based computer vision and identify future research opportunities based on one of our practical use cases. ... mehr


Volltext §
DOI: 10.5445/IR/1000158840
Veröffentlicht am 12.07.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Institut für Wirtschaftsinformatik und Marketing (IISM)
Karlsruhe Service Research Institute (KSRI)
Publikationstyp Hochschulschrift
Publikationsdatum 12.07.2023
Sprache Englisch
Identifikator KITopen-ID: 1000158840
Verlag Karlsruher Institut für Technologie (KIT)
Umfang xv, 249 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Wirtschaftswissenschaften (WIWI)
Institut Institut für Wirtschaftsinformatik und Marketing (IISM)
Prüfungsdatum 11.04.2023
Referent/Betreuer Satzger, Gerhard
Färber, Michael
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