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  • We present an approach to constructing a model of the universe for explaining observations and making decisions based on learning new concepts. We use a weak statistical model, e.g. a discriminative classifier, to distinguish errors in measurements from improper modeling. We use boolean logic to combine outcomes of direct detectors of relevant events, e.g. presence of sound and presence of human shape in the field of view, into more complex models explaining the states in which the universe may appear. The process of constructing a new concept is initiated when a significant disagreement - incongruence -- has been observed between incoming data and the current model of the universe. Then, a new concept, i.e. a new direct detector, is trained on incongruent data and combined with existing models to remove the incongruence. We demonstrate the concept in an experiment with human audio-visual detection.
  • We present an approach to constructing a model of the universe for explaining observations and making decisions based on learning new concepts. We use a weak statistical model, e.g. a discriminative classifier, to distinguish errors in measurements from improper modeling. We use boolean logic to combine outcomes of direct detectors of relevant events, e.g. presence of sound and presence of human shape in the field of view, into more complex models explaining the states in which the universe may appear. The process of constructing a new concept is initiated when a significant disagreement - incongruence -- has been observed between incoming data and the current model of the universe. Then, a new concept, i.e. a new direct detector, is trained on incongruent data and combined with existing models to remove the incongruence. We demonstrate the concept in an experiment with human audio-visual detection. (en)
Title
  • Learning from Incongruence
  • Learning from Incongruence (en)
skos:prefLabel
  • Learning from Incongruence
  • Learning from Incongruence (en)
skos:notation
  • RIV/68407700:21230/12:00200333!RIV13-MSM-21230___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6840770038)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 146642
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/12:00200333
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Incongruence; Audio-visual data processing (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [6708788B1120]
http://linked.open...v/mistoKonaniAkce
  • Barcelona
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...i/riv/nazevZdroje
  • Detection and Identification of Rare Audiovisual Cues
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Heller, Jan
  • Pajdla, Tomáš
  • Havlena, Michal
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000302002500011
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
issn
  • 1860-949X
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-24034-8_10
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-24033-1
http://localhost/t...ganizacniJednotka
  • 21230
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