DocumentCode
240547
Title
Combined linguistic and sensor models for machine learning
Author
Ilin, Roman
Author_Institution
Air Force Res. Lab., Wright-Patterson AFB, OH, USA
fYear
2014
fDate
9-12 Dec. 2014
Firstpage
24
Lastpage
30
Abstract
This work builds on a cognitive theory called dynamic logic and considers the relationship between language and cognition. We explore the idea of dual models that combine linguistic and sensor features. We demonstrate that simultaneous learning of textual and image data results in formation of meaningful concepts and subsequent improvement in concept recognition.
Keywords
learning (artificial intelligence); pattern recognition; sensor fusion; cognitive theory; concept recognition; dynamic logic; image data learning; linguistic model; machine learning; sensor model; textual data learning; Acceleration; Computational modeling; Data models; Mathematical model; Numerical models; Pragmatics; Vectors; Dynamic Logic; LUPI; Language and Cognition; Unsupervised Learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), 2014 IEEE Symposium on
Conference_Location
Orlando, FL
Type
conf
DOI
10.1109/CCMB.2014.7020690
Filename
7020690
Link To Document