Transformationally Identical and Invariant Convolutional Neural Networks by Combining Symmetric Operations or Input Vectors

Transformationally invariant processors constructed by transformed input vectors or operators have been suggested and applied to many applications. In this study, transformationally identical processing based on combining results of all sub-processes with corresponding transformations at one of the...

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Veröffentlicht in:	arXiv.org 2018-08
Hauptverfasser:	Lo, ShihChung B, Freedman, Matthew T, Mun, Seong K
Format:	Artikel
Sprache:	eng
Schlagworte:	Activation Artificial neural networks Equivalence Invariants Mathematical analysis Neural networks Transformations (mathematics) Vectors (mathematics)
Online-Zugang:	Volltext
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