Patent ID: 11934478
Assignee: THE UNIVERSITY OF CHICAGO
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 10:
11. A computing system configured for computationally processing data with a multi-layer convolutional neural network (CNN), the computing system comprising:
one or more processors; and
memory configured to store computer-executable instructions that, when executed by the one or more processors, cause the computing system to carry out operations including:
implementing the multi-layer CNN in an architectural form having an input layer, an output layer, and one or more intermediate layers, from a first intermediate layer to a last intermediate layer;
receiving digital image data corresponding to input data that are represented in a form of evaluations of one or more continuous functions on a sphere;
at the input layer:
inputting the input data to the input layer;
computing covariant Fourier space activations by analytically transforming the one or more continuous functions into spherical harmonic expansions of the input data; and
outputting the computed covariant Fourier space activations to the first intermediate layer;

at each intermediate layer:
receiving as input activations from an immediately-preceding layer of the CNN;
processing the received input activations by applying Clebsch-Gordan transforms to compute respective covariant Fourier space activations without computing any intermediate inverse Fourier transforms or forward Fourier transforms; and
outputting the computed respective covariant Fourier space activations to an immediately next layer of the CNN;

at the output layer:
receiving as input the computed covariant Fourier space activations of the last intermediate layer;
processing the received covariant Fourier activations of the last intermediate layer by computing invariant activations; and
outputting the computed invariant activations.