DMNAS: Differentiable Multi-modal Neural Architecture Search

Yushiro Funoki; Satoshi Ono

doi:10.1117/12.2590792

13 March 2021 DMNAS: Differentiable Multi-modal Neural Architecture Search

Yushiro Funoki, Satoshi Ono

Proceedings Volume 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021; 117662B (2021) https://doi.org/10.1117/12.2590792
Event: International Workshop on Advanced Imaging Technology 2021 (IWAIT 2021), 2021, Online Only

Abstract

This paper proposes a Neural Architecture Search (NAS) method for multimodal sequential data using a gradient-based neural architecture search method named Differentiable Neural Architecture Search (DARTS). Because Deep Neural Networks (DNNs) for multimodal data require task-specific network architecture, there is a high need for NAS for them to reduce the labor of architecture design. Experimental results using an emotion recognition dataset containing sequential data showed that the proposed method succeeded in automatically designing a network architecture with competitive performance to manually designed networks.

Citation Download Citation

Yushiro Funoki and Satoshi Ono "DMNAS: Differentiable Multi-modal Neural Architecture Search", Proc. SPIE 11766, International Workshop on Advanced Imaging Technology (IWAIT) 2021, 117662B (13 March 2021); https://doi.org/10.1117/12.2590792

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