Phenomenological Model for the Adapatation of Shape-Selective Neurons in Area IT

Giese MA, Kuravi P, Vogels R (2016)
In: Artificial Neural Networks and Machine Learning (ICANN 2016). Springer International Publishing: 222--229.

Sammelwerksbeitrag | Englisch
 
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Autor/in
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Einrichtung
Erscheinungsjahr
2016
Buchtitel
Artificial Neural Networks and Machine Learning (ICANN 2016)
Seite(n)
222--229
Page URI
https://pub.uni-bielefeld.de/record/2918906

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Giese MA, Kuravi P, Vogels R. Phenomenological Model for the Adapatation of Shape-Selective Neurons in Area IT. In: Artificial Neural Networks and Machine Learning (ICANN 2016). Springer International Publishing; 2016: 222--229.
Giese, M. A., Kuravi, P., & Vogels, R. (2016). Phenomenological Model for the Adapatation of Shape-Selective Neurons in Area IT. Artificial Neural Networks and Machine Learning (ICANN 2016), 222--229. Springer International Publishing. doi:10.1007/978-3-319-44778-0_26
Giese, M. A., Kuravi, P., and Vogels, R. (2016). “Phenomenological Model for the Adapatation of Shape-Selective Neurons in Area IT” in Artificial Neural Networks and Machine Learning (ICANN 2016) (Springer International Publishing), 222--229.
Giese, M.A., Kuravi, P., & Vogels, R., 2016. Phenomenological Model for the Adapatation of Shape-Selective Neurons in Area IT. In Artificial Neural Networks and Machine Learning (ICANN 2016). Springer International Publishing, pp. 222--229.
M.A. Giese, P. Kuravi, and R. Vogels, “Phenomenological Model for the Adapatation of Shape-Selective Neurons in Area IT”, Artificial Neural Networks and Machine Learning (ICANN 2016), Springer International Publishing, 2016, pp.222--229.
Giese, M.A., Kuravi, P., Vogels, R.: Phenomenological Model for the Adapatation of Shape-Selective Neurons in Area IT. Artificial Neural Networks and Machine Learning (ICANN 2016). p. 222--229. Springer International Publishing (2016).
Giese, Martin A., Kuravi, Pradeep, and Vogels, Rufin. “Phenomenological Model for the Adapatation of Shape-Selective Neurons in Area IT”. Artificial Neural Networks and Machine Learning (ICANN 2016). Springer International Publishing, 2016. 222--229.

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