DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Minkyu | ko |
dc.contributor.author | Tani, Jun | ko |
dc.date.accessioned | 2023-08-04T05:01:12Z | - |
dc.date.available | 2023-08-04T05:01:12Z | - |
dc.date.created | 2023-07-07 | - |
dc.date.created | 2023-07-07 | - |
dc.date.issued | 2017-05 | - |
dc.identifier.citation | 2017 International Joint Conference on Neural Networks, IJCNN 2017, pp.657 - 664 | - |
dc.identifier.uri | http://hdl.handle.net/10203/311163 | - |
dc.description.abstract | The current paper presents a novel recurrent neural network model, predictive multiple spatio-temporal scales RNN (P-MSTRNN), which can generate as well as recognize dynamic visual patterns in a predictive coding framework. The model is characterized by multiple spatio-temporal scales imposed on neural unit dynamics through which an adequate spatio-temporal hierarchy develops via learning from exemplars. The model was evaluated by conducting an experiment of learning a set of whole body human movement patterns, which was generated by following a hierarchically defined movement syntax. The analysis of the trained model clarifies what types of spatio-temporal hierarchy develops in dynamic neural activity as well as how robust generation and recognition of movement patterns can be achieved by using the error minimization principle. | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Predictive coding for dynamic vision: Development of functional hierarchy in a multiple spatio-temporal scales RNN model | - |
dc.type | Conference | - |
dc.identifier.wosid | 000426968700088 | - |
dc.identifier.scopusid | 2-s2.0-85030991444 | - |
dc.type.rims | CONF | - |
dc.citation.beginningpage | 657 | - |
dc.citation.endingpage | 664 | - |
dc.citation.publicationname | 2017 International Joint Conference on Neural Networks, IJCNN 2017 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Anchorage, AK | - |
dc.identifier.doi | 10.1109/IJCNN.2017.7965915 | - |
dc.contributor.localauthor | Tani, Jun | - |
dc.contributor.nonIdAuthor | Choi, Minkyu | - |
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