Dendritic Learning-Incorporated Vision Transformer for Image Recognition
Zhiming Zhang, Zhenyu Lei, Masaaki Omura, Hideyuki Hasegawa, Shangce Gao
Abstract
This letter proposes to integrate dendritic learnable network architecture with Vision Transformer to improve the accuracy of image recognition. In this study, based on the theory of dendritic neurons in neuroscience, we design a network that is more practical for engineering to classify visual features. Based on this, we propose a dendritic learning-incorporated vision Transformer (DVT), which out-performs other state-of-the-art methods on three image recognition benchmarks.
Topics & Concepts
TransformerComputer scienceArtificial intelligenceArchitectureComputer visionPattern recognition (psychology)EngineeringElectrical engineeringVoltageVisual artsArtAdvanced Memory and Neural ComputingNeural Networks and ApplicationsCCD and CMOS Imaging Sensors