A Meta-Learning-Based Recognition Method for Multidimensional Feature Extraction and Fusion of Underwater Targets
To tackle the challenges of relative attitude adaptability and limited sample availability in underwater moving target recognition for active sonar, this study focuses on key aspects such as feature extraction, network model design, and information fusion. A pseudo-three-dimensional spatial feature...
Saved in:
| Main Authors: | Xiaochun Liu, Yunchuan Yang, Youfeng Hu, Xiangfeng Yang, Liwen Liu, Lei Shi, Jianguo Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/10/5744 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Modulation recognition of underwater acoustic communication signals based on deep learning
by: Biao Wang, et al.
Published: (2024-12-01) -
Optimization Strategy for Underwater Target Recognition Based on Multi-Domain Feature Fusion and Deep Learning
by: Yanyang Lu, et al.
Published: (2025-07-01) -
Research on Underwater Acoustic Target Recognition Based on a 3D Fusion Feature Joint Neural Network
by: Weiting Xu, et al.
Published: (2024-11-01) -
Multi-Scale Feature Fusion Enhancement for Underwater Object Detection
by: Zhanhao Xiao, et al.
Published: (2024-11-01) -
UW-DETR: Feature Fusion Enhanced RT-DETR for Improving Underwater Object Detection
by: Xingkun Li, et al.
Published: (2024-01-01)