Objective Recognition and Detection in Marine Engineering
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Marine Science and Engineering".
Deadline for manuscript submissions: 20 October 2026 | Viewed by 173
Special Issue Editors
Interests: aeromagnetic survey; magnetic anomaly detection; visual saliency modeling; sar target detection; machine learning; deep neural networks
Interests: magnetic targeting; magnetic communication; ELF field analysis; IoT
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Object detection and recognition play a crucial role in marine engineering, which can facilitate real-time target sensing and information acquisition on both the sea surface and underwater. Currently, various high-performance sensors and their carrying platforms are being developed to collect information on objects of interest in marine observation scenarios. By comprehensively exploiting the physical properties of marine targets, different types of marine observation data can be collected for interpreting and understanding tasks. Due to the limitations of a single physical-field sensor, interferences from sensor-carrying platforms, noises of the surrounding marine environment, and the complex cognitive patterns of marine targets, fast and accurate detection and recognition of marine objects are still ongoing issues. Recently, the rapid development of deep learning techniques has brought new inspiration to this field, and new models and algorithms have been proposed to better tackle the abovementioned challenges. Hopefully, this will further promote the technical development of object detection and recognition in marine engineering.
For this Special Issue, we are therefore interested in receiving articles that investigate marine object detection and recognition by means of advanced sensor and interpretation techniques. Potential research topics include, but are not limited to, the following:
- Deep learning for marine target detection and recognition;
- Small-sample learning and feature knowledge transfer;
- Multi-sensor data fusion for marine target sensing;
- Calibration and compensation of sensor measurement error;
- Suppression and elimination of carrying platform interference;
- Marine noise characteristic analysis and denoising;
- Spaceborne and airborne marine target surveillance;
- Underwater acoustic detection and recognition;
- Aeromagnetic survey for marine target detection;
- Synthetic aperture radar for surface ship detection;
- Magnetic anomaly detection and localization;
- Unmanned underwater vehicle for target detection.
Dr. Shigang Wang
Dr. Yang Ke
Guest Editors
Manuscript Submission Information
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Keywords
- marine remote sensing
- deep learning
- target detection and recognition
- feature extraction and fusion
- noise interference suppression
- image and signal processing
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