CONSTRUCTION OF NEURAL ARCHITECTURES WITH DESIRED BEHAVIOUR UNDER GEOMETRIC TRANSFORMATIONS OF THE INPUT | Zendy

Viacheslav Dudar | Zendy; V. V. Semenov | Zendy

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CONSTRUCTION OF NEURAL ARCHITECTURES WITH DESIRED BEHAVIOUR UNDER GEOMETRIC TRANSFORMATIONS OF THE INPUT

Author(s) -

Viacheslav Dudar,

V. V. Semenov

Publication year - 2020

Publication title -

journal of numerical and applied mathematics

Language(s) - English

Resource type - Journals

eISSN - 2706-9699

pISSN - 2706-9680

DOI - 10.17721/2706-9699.2020.1.03

Subject(s) - convolutional neural network , geometric transformation , transformation (genetics) , transformation geometry , computer science , pixel , geometric pattern , algorithm , geometric modeling , simple (philosophy) , geometric shape , artificial intelligence , mathematics , image (mathematics) , geometry , biochemistry , gene , philosophy , epistemology , chemistry

We present a general method for analysis of convolutional layers under geometric transformations of the input that are linear with respect to pixel values. We also describe the algorithm for finding all possible types of behaviours of the output of convolutional layers under geometric transformations of the input. We also present a general method for construction of convolutional architectures with desired behaviour under geometric transformations of the input.

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