Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00196128" target="_blank" >RIV/68407700:21230/12:00196128 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/TPAMI.2011.279" target="_blank" >http://dx.doi.org/10.1109/TPAMI.2011.279</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TPAMI.2011.279" target="_blank" >10.1109/TPAMI.2011.279</a>
Alternative languages
Result language
angličtina
Original language name
Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
Original language description
Unexpected stimuli are a challenge to any machine learning algorithm. Here we identify distinct types of unexpected events, when general level and specific level classifiers give conflicting predictions. We define a formal framework for the representation and processing of incongruent events: Starting from the notion of label hierarchy, we show how partial order on labels can be deduced from such hierarchies. For each event, we compute its probability in different ways, based on adjacent levels in the label hierarchy. An incongruent event is an event where the probability computed based on some more specific level is much smaller than the probability computed based on some more general level, leading to conflicting predictions. Algorithms are derived to detect incongruent events from different types of hierarchies, different applications and a variety of data types. We present promising results for the detection of novel visual and audio objects, and new patterns of motion in video. We
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Pattern Analysis and Machine Intelligence
ISSN
0162-8828
e-ISSN
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Volume of the periodical
34
Issue of the periodical within the volume
10
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
1886-1901
UT code for WoS article
000307522700002
EID of the result in the Scopus database
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