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A Symbolic Approach for Explaining Errors in Image Classification Tasks
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-4001-2087
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-0579-7181
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0001-7562-2443
Örebro University, School of Science and Technology. (AASS)ORCID iD: 0000-0002-3122-693X
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Machine learning algorithms, despite their increasing success in handling object recognition tasks, still seldom perform without error. Often the process of understanding why the algorithm has failed is the task of the human who, using domain knowledge and contextual information, can discover systematic shortcomings in either the data or the algorithm. This paper presents an approach where the process of reasoning about errors emerging from a machine learning framework is automated using symbolic techniques. By utilizing spatial and geometrical reasoning between objects in a scene, the system is able to describe misclassified regions in relation to its context. The system is demonstrated in the remote sensing domain where objects and entities are detected in satellite images.

Place, publisher, year, edition, pages
2018.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:oru:diva-68000OAI: oai:DiVA.org:oru-68000DiVA, id: diva2:1233674
Conference
27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, July 13-19, 2018
Note

IJCAI Workshop on Learning and Reasoning: Principles & Applications to Everyday Spatial and Temporal Knowledge

Available from: 2018-07-18 Created: 2018-07-18 Last updated: 2018-07-26Bibliographically approved

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Alirezaie, MarjanLängkvist, MartinSioutis, MichaelLoutfi, Amy

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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf