Please use this identifier to cite or link to this item:
https://doi.org/10.1109/CIHLI.2013.6613261
DC Field | Value | |
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dc.title | Perception and prediction - A connectionist model | |
dc.contributor.author | Iyer, L.R. | |
dc.contributor.author | Ho, S.-B. | |
dc.date.accessioned | 2014-11-28T01:54:21Z | |
dc.date.available | 2014-11-28T01:54:21Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Iyer, L.R.,Ho, S.-B. (2013). Perception and prediction - A connectionist model. Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Human-Like Intelligence, CIHLI 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 : 25-32. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/CIHLI.2013.6613261" target="_blank">https://doi.org/10.1109/CIHLI.2013.6613261</a> | |
dc.identifier.isbn | 9781467359238 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/111628 | |
dc.description.abstract | Generating appropriate responses to incoming stimuli is a fundamental task of an organism. However, in order to generate intelligent responses, it is important to have a deeper understanding of the environment, and make predictions based on this knowledge. Although the ability to make predictions is intrinsic in humans and many animals, it is still a difficult task for a machine with no in built knowledge about the situation. In this paper we present a biologically inspired neural network model that predicts the future trajectory of a moving object after observing its current trajectory. © 2013 IEEE. | |
dc.description.uri | http://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/CIHLI.2013.6613261 | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | TEMASEK LABORATORIES | |
dc.description.doi | 10.1109/CIHLI.2013.6613261 | |
dc.description.sourcetitle | Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Human-Like Intelligence, CIHLI 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 | |
dc.description.page | 25-32 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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