Constructing Convolutional Neural Networks Based on Quaternion


연구 분야: Artificial Intelligence



학회: 2020 International Joint Conference on Neural Networks (IJCNN)


초록

A convolutional neural network based on quaternion, a four-dimensional hypercomplex number system, is proposed and evaluated in this paper. Called Quaternionic Convolutional Neural Networks (QCNNs), these networks can accept and operate three-dimensional signals by neurons in the networks. The performances of the proposed networks are investigated through classification of CIFAR-10 color images, and it is shown that the proposed QCNN outperforms a conventional (real-valued) CNN.


Author Profile
Shuto Hongo

Graduate School of Engineering University of Hyogo Hyogo Japan

Japan
Author Profile
Teijiro Isokawa

Graduate School of Engineering University of Hyogo Hyogo Japan

Japan
Author Profile
Nobuyuki Matsui

University of Hyogo Hyogo Japan

Japan

📄 논문 정보

발행 연도 2020년
인용수 9
출판 국가 Japan
사이트 IEEE
좋아요 수 0

연관 논문 목록 (162건)