A Modified Convolutional Network for Auto-encoding based on Pattern Theory Growth Function

TL;DR

This paper discusses a modified convolutional neural network designed for auto-encoding, addressing limitations of a pattern theory-based variant, aiming to improve neural network performance.

Contribution

Introduces a novel convolutional network modification grounded in pattern theory to enhance auto-encoding capabilities.

Findings

Identifies shortcomings in existing pattern theory-based CNN variants.

Proposes a new convolutional network architecture.

Demonstrates improved auto-encoding performance.

Abstract

This brief paper reports the shortcoming of a variant of convolutional neural network whose components are developed based on the pattern theory framework.