Tessarine and Quaternion-Valued Deep Neural Networks for Image Classification

  • Fernando Ribeiro de Senna UNICAMP
  • Marcos Eduardo Valle UNICAMP


Many image processing and analysis tasks are performed with deep neural networks. Although the vast majority of advances have been made with real numbers, recent works have shown that complex and hypercomplex-valued networks may achieve better results. In this paper, we address quaternion-valued and introduce tessarine-valued deep neural networks, including tessarine-valued 2D convolutions. We also address initialization schemes and hypercomplex batch normalization. Finally, a tessarine-valued ResNet model with hypercomplex batch normalization outperformed the corresponding real and quaternion-valued networks on the CIFAR dataset.


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SENNA, Fernando Ribeiro de; VALLE, Marcos Eduardo. Tessarine and Quaternion-Valued Deep Neural Networks for Image Classification. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 18. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 350-361. ISSN 2763-9061. DOI: https://doi.org/10.5753/eniac.2021.18266.