Deep Hypercomplex Networks for Spatiotemporal Data Processing: Parameter efficiency and superior performance [Hypercomplex Signal and Image Processing]-Reference-Cited by-同舟云学术

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Deep Hypercomplex Networks for Spatiotemporal Data Processing: Parameter efficiency and superior performance [Hypercomplex Signal and Image Processing]

Published:2024-05 Issue:3 Volume:41 Page:101-112
ISSN:1053-5888
Container-title:IEEE Signal Processing Magazine
language:
Short-container-title:IEEE Signal Process. Mag.

Author:

Bojesomo Alabi¹^ORCID,Liatsis Panos²^ORCID,Marzouqi Hasan Al¹^ORCID

Affiliation:

1. Department of Electrical Engineering and Computer Science, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates

2. Department of Computer Science, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/79/10640314/10640320.pdf?arnumber=10640320

Reference30 articles.

1. Exploring Highly Efficient Compact Neural Networks For Image Classification

2. Deep octonion networks

3. Deep Learning With Edge Computing: A Review

4. MobileNetV2: Inverted Residuals and Linear Bottlenecks

5. CondenseNet: An Efficient DenseNet Using Learned Group Convolutions

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