Deep learning object detection as an assistance system for complex image labeling tasks

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dc.contributor.authorLeimkühler, Max
dc.contributor.authorGravemeier, Laura Sophie
dc.contributor.authorBiester, Tim
dc.contributor.authorThomas, Oliver
dc.date.accessioned2020-12-24T19:01:57Z
dc.date.available2020-12-24T19:01:57Z
dc.date.issued2021-01-05
dc.description.abstractObject detection via deep learning has many promising areas of application. However, robustness and accuracy of fully automated systems are often insufficient for practical use. Integrating results from Artificial Intelligence (AI) and human intelligence in collaborative settings might bridge the gap between efficiency and accuracy. This study proves increased efficiency when supporting human intelligence through AI without negative impact on effectiveness in a fine- grained car scratch image labeling task. Based on the confirmed benefits of AI with human intelligence in the loop approaches, this contribution discusses potential practical application scenarios and envisions the implementation of assistance systems supported by computer vision.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.039
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70650
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCollaboration with Cognitive Assistants and AI
dc.subjectassistance system
dc.subjecthuman-ai collaboration
dc.subjecthuman in the loop
dc.subjectimage labeling
dc.subjectobject detection
dc.titleDeep learning object detection as an assistance system for complex image labeling tasks
prism.startingpage328

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