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Underwater object detection for smooth and autonomous operations of naval missions: a pilot Dataset.

Yan, Yijun; Li, Yinhe; Lin, Hanhe; Sarker, Md Mostafa Kamal; Ren, Jinchang; McCall, John

Authors

Yijun Yan

Hanhe Lin

Md Mostafa Kamal Sarker



Contributors

Amir Hussain
Editor

Iman Yi Liao
Editor

Rongjun Chen
Editor

Kaizhu Huang
Editor

Huimin Zhao
Editor

Xiaoyong Liu
Editor

Thomas Maul
Editor

Abstract

Underwater object detection is essential for ensuring autonomous naval operations. However, this task is challenging due to the complexities of underwater environments that often degrade image quality, thereby hampering the performance of detection and classification systems. On the other hand, the absence of a readily available dataset complicates the development and evaluation of underwater object detection approaches, particularly for deep learning approaches. To address this bottleneck, we have created a new dataset, called National Subsea Centre Underwater Images (NSCUI). It is comprised of 243 images, divided into three subsets that are captured in bright, low-light, and dark environments, respectively. To validate the utility of this dataset, we implemented three popular deep learning models in our experiments. We believe that the annotated NSCUI will significantly advance the development of underwater object detection through the application of deep learning techniques.

Citation

YAN, Y., LI, Y., LIN, H., SARKER, M.M.K., REN, J. and MCCALL, J. 2024. Underwater object detection for smooth and autonomous operations of naval missions: a pilot dataset. In: Ren, J., Hussain, A., Liao, I.Y. et al. (eds.) Advances in brain inspired cognitive systems: proceedings of the 13th Brain-inspired cognitive systems 2023 (BICS 2023), 5-6 August 2023, Kuala Lumpur, Malaysia. Lecture notes in computer sciences, 14374. Cham: Springer [online], pages 113-122. Available from: https://doi.org/10.1007/978-981-97-1417-9_11

Conference Name 13th Brain-inspired cognitive systems international conference 2023 (BICS 2023)
Conference Location Kuala Lumpur, Malaysia
Start Date Aug 5, 2023
End Date Aug 6, 2023
Acceptance Date Jul 28, 2023
Online Publication Date May 22, 2024
Publication Date Dec 31, 2024
Deposit Date Jun 13, 2024
Publicly Available Date May 23, 2025
Publisher Springer
Pages 113-122
Series Title Lecture notes in computer science (LNCS)
Series Number 14374
Series ISSN 0302-9743; 1611-3349
Book Title Advances in brain inspired cognitive systems
ISBN 9789819714162
DOI https://doi.org/10.1007/978-981-97-1417-9_11
Keywords Underwater object detection; Image enhancement; Deep learning
Public URL https://rgu-repository.worktribe.com/output/2372862