Scene understanding through Deep Learning

  • Recent work in image captioning and scene-segmentation has shown significant results in the context of scene-understanding. However, most of these developments have not been extrapolated to research areas such as robotics. In this work we review the current state-ofthe- art models, datasets and metrics in image captioning and scenesegmentation. We introduce an anomaly detection dataset for the purpose of robotic applications, and we present a deep learning architecture that describes and classifies anomalous situations. We report a METEOR score of 16.2 and a classification accuracy of 97 %.

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Metadaten
Document Type:Report
Language:English
Pagenumber:77
ISBN:978-3-96043-045-2
ISSN:1869-5272
URN:urn:nbn:de:hbz:1044-opus-30422
DOI:https://doi.org/10.18418/978-3-96043-045-2
Advisor:Paul G. Plöger, Matías Valdenegro
Publishing Institution:Hochschule Bonn-Rhein-Sieg
Date of first publication:2017/05/29
Series (Volume):Technical Report / Hochschule Bonn-Rhein-Sieg - University of Applied Sciences, Department of Computer Science (02-2017)
Tag:METEOR score; Scene understanding through Deep Learning; image captioning; robotics; scene-segmentation
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):000 Informatik, Informationswissenschaft, allgemeine Werke / 000 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2017/05/29
Licence (German):License Logokostenfreier Zugang, Rechte vorbehalten