Using the Choquet Integral in the Pooling Layer in Deep Learning Networks

Author:

Dias Camila Alves,Bueno Jéssica C. S.,Borges Eduardo N.,Botelho Silvia S. C.,Dimuro Graçaliz Pereira,Lucca Giancarlo,Fernandéz Javier,Bustince Humberto,Drews Junior Paulo Lilles Jorge

Publisher

Springer International Publishing

Reference24 articles.

1. Agarap, A.F.: An Architecture Combining Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for Image Classification. Adamson University, Manila (2017)

2. Lecture Notes in Computer Science;A Ahmed,2008

3. Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions: A Guide for Practitioners, vol. 221. Springer, Berlin/Heidelberg (2007). https://doi.org/10.1007/978-3-540-73721-6

4. Boureau, Y.L., Ponce, J., Lecun, Y.: A theoretical analysis of feature pooling in visual recognition. In: Proceedings of the 27th International Conference on Machine Learning (ICML-2010), Haifa, Israel, pp. 111–118 (2010)

5. Choquet, G.: Theory of capacities. In: Annales de l’institut Fourier, Grenoble, France, vol. 5, pp. 131–295 (1954)

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