ODMTCNet: An Interpretable Multi-view Deep Neural Network Architecture for Image Feature Representation
Year: 2021
Type: preprint
Abstract: This work proposes an interpretable multi-view deep neural network architecture, namely optimal discriminant multi-view tensor convolutional network (ODMTCNet), by integrating statistical machine learning (SML) principles with the deep neural network (DNN) architecture.
Source: arXiv (Cornell University)
Authors: Gao, Lei, Guo, Zheng, Guan, Ling
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3209056655