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Intelligent Marine Technology and Systems is a peer-reviewed journal published by Springer Nature, covering Underwater Acoustics Research, Image Enhancement Techniques, Underwater Vehicles and Communication Systems.
| Publisher | Springer Nature |
|---|---|
| Reference style | Superscript numbered (Nature) Superscript — small raised numerals in the text 1. Smith, A., Jones, B. & Lee, C. A representative article title. Intelligent Marine Technology and Systems 12, 45–58 (2023).
Formats any DOI in Intelligent Marine Technology and Systems style. No sign-up. |
| Publishes research in | Underwater Acoustics Research Image Enhancement Techniques Underwater Vehicles and Communication Systems Advanced Neural Network Applications Oceanographic and Atmospheric Processes |
| ISSN | 2948-1953 |
| Citation impact (2-yr) | 3.52 |
| h-index | 11 |
| i10-index | 14 |
| Total citations | 602 |
| Top institutions publishing here | Ocean University of China |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Abstract The rapidly growing exploitation and utilization of marine resources by humans has sparked considerable interest in underwater object detection tasks. Targets captured in underwater environments differ significantly from those captured in general images owing to various factors, such as water turbidity, complex background conditions, and lighting variations. These adverse factors pose a host of…
Abstract As marine resources continue to be exploited, the remarkable locomotion and coordination of fish provide an excellent source of inspiration for scientists and engineers to design and control the next -generation autonomous underwater vehicles within a bionic framework. Underwater biomimetic robots combine bionics and robot technology, and their biological characteristics offer a lot of…
Abstract The forthcoming wave of progress in oceanographic technology is the digital twin of the ocean, a concept that integrates marine big data and artificial intelligence (AI). This development is a logical consequence of combining data science and marine science and is considered superior to previous models, such as the digital ocean, transparent ocean, and…
Abstract Recent advancements in machine learning (ML) techniques applied to underwater acoustics have significantly impacted various aspects of this field, such as source localization, target recognition, communication, and geoacoustic inversion. This review provides a comprehensive summary and evaluation of these developments. As a data-driven approach, ML played a pivotal role in discerning intricate relationships between…
Abstract Underwater images are often influenced by color casts, low contrast, and blurred details. We observe that images taken in natural settings typically have similar histograms across color channels, while underwater images do not. To improve the natural appearance of an underwater image, it is critical to improve the histogram similarity across its color channels.…
