Integrating multi-sensory input in the body model – a RNN approach to connect proprioception, visual features and motor control

Schilling M (2011)
In: Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA).

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Erscheinungsjahr
2011
Titel des Konferenzbandes
Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA)
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https://pub.uni-bielefeld.de/record/2284314

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Schilling M. Integrating multi-sensory input in the body model – a RNN approach to connect proprioception, visual features and motor control. In: Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA). 2011.
Schilling, M. (2011). Integrating multi-sensory input in the body model – a RNN approach to connect proprioception, visual features and motor control. Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA)
Schilling, M. (2011). “Integrating multi-sensory input in the body model – a RNN approach to connect proprioception, visual features and motor control” in Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA).
Schilling, M., 2011. Integrating multi-sensory input in the body model – a RNN approach to connect proprioception, visual features and motor control. In Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA).
M. Schilling, “Integrating multi-sensory input in the body model – a RNN approach to connect proprioception, visual features and motor control”, Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA), 2011.
Schilling, M.: Integrating multi-sensory input in the body model – a RNN approach to connect proprioception, visual features and motor control. Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA). (2011).
Schilling, Malte. “Integrating multi-sensory input in the body model – a RNN approach to connect proprioception, visual features and motor control”. Proceedings of the International Joint Conference on Neural Networks 2011, San Jose (CA). 2011.
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