Study on bottom sediment classification by complementary use of seafloor images and environmental sounds

Shota Takaki; Masahiro Migita; Masashi Toda

doi:10.1117/12.2626087

30 April 2022 Study on bottom sediment classification by complementary use of seafloor images and environmental sounds

Shota Takaki, Masahiro Migita, Masashi Toda

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 1217716 (2022) https://doi.org/10.1117/12.2626087
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

In CNN-based classification for seafloor images, the accuracy may decrease drastically in different sea areas. Therefore, we aim to improve the accuracy by utilizing the dragged environmental sound. Classification by sound includes classification by CNN using logmel images, and we can expect a complementary relationship by using classification by image and sound together. As a concrete method, we propose a robust sediment classification method using transfer learning.

Citation Download Citation

Shota Takaki, Masahiro Migita, and Masashi Toda "Study on bottom sediment classification by complementary use of seafloor images and environmental sounds", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 1217716 (30 April 2022); https://doi.org/10.1117/12.2626087

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KEYWORDS

Image classification

Data modeling

Video

Acoustics

Cameras

Convolution

Visualization

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