Dendritic Convolutional Neural Network

Rong‐Long Wang, Zhenyu Lei, Zhiming Zhang, Shangce Gao

2021IEEJ Transactions on Electrical and Electronic Engineering24 citationsDOI

Abstract

Abstract Convolutional neural network (CNN), as one of the mainstream deep learning models, has achieved great success in image recognition. All neurons used in CNN are based on the McCulloch‐Pitts model, which is over‐simplified. To further improve CNN's learning capacity, this paper proposes a novel dendritic CNN (DCNN), which considers the nonlinear information processing functions of dendrites in a single neuron. The superiority of DCNN is confirmed based on four widely used image recognition tasks. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Topics & Concepts

Convolutional neural networkComputer scienceArtificial intelligenceDeep learningNeocognitronMainstreamCellular neural networkPattern recognition (psychology)Artificial neural networkImage (mathematics)Time delay neural networkPhilosophyTheologyNeural Networks and ApplicationsThermography and Photoacoustic TechniquesMachine Learning and ELM