journal article·2025Open access

Marine Ship Detection Based on Twin Feature Pyramid Network and Spatial Attention

Huagang Jin, Yu Zhou

Computers, Materials & Continua· Volume 85· Issue 1

Abstract

Recently, ship detection technology has been applied extensively in the marine security monitoring field. However, achieving accurate marine ship detection still poses significant challenges due to factors such as varying sca... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Measurement and Detection Methods · Infrared Target Detection Methodologies · Industrial Vision Systems and Defect Detection

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (32)

Show source-provided references
1. Ship detection in optical remote sensing images based on deep convolutional neural networks10.1117/1.JRS.11.042611 ↗
2. Dense attention pyramid networks for multi-scale ship detection in SAR images10.1109/TGRS.2019.2923988 ↗
3. Introduction to mathematical morphology10.1016/0734-189X(86)90002-2 ↗
4. State-of-the-art in visual attention modeling10.1109/TPAMI.2012.89 ↗
5. Speeded-up robust features (SURF)10.1016/j.cviu.2007.09.014 ↗
6. Validation of ship detection by the RADARSAT synthetic aperture radar and the ocean monitoring workstation10.1080/07038992.2000.10874770 ↗
7. Rich feature hierarchies for accurate object detection and semantic segmentation
8. Fast R-CNN
9. Faster R-CNN: towards real-time object detection with region proposal networks10.1109/TPAMI.2016.2577031 ↗
10. SSD: single shot multibox detector
11. You only look once: unified, real-time object detection
12. Feature pyramid networks for object detection
13. Attention-based fusion factor in FPN for object detection10.1007/s10489-022-03220-0 ↗
14. Dual-bottleneck feature pyramid network for multiscale object detection10.1117/1.JEI.31.1.013009 ↗
15. Effective fusion factor in FPN for tiny object detection
16. High-level semantic networks for multi-scale object detection10.1109/TCSVT.2019.2950526 ↗
17. AugFPN: improving multi-scale feature learning for object detection
18. NAS-FPN: learning scalable feature pyramid architecture for object detection
19. EfficientDet: scalable and efficient object detection
20. Adaptive region-aware feature enhancement for object detection10.1016/j.patcog.2021.108437 ↗
21. Attention-based network for low-light image enhancement
22. Squeeze-and-excitation networks
23. CBAM: convolutional block attention module
24. Attention over attention: an enhanced supervised video summarization approach10.1016/j.procs.2023.01.211 ↗
25. Bearing faulty prognostic approach based on multiscale feature extraction and attention learning mechanism10.1155/2021/6221545 ↗
26. Language and vision based person re-identification for surveillance systems using deep learning with LIP layers10.1016/j.imavis.2023.104658 ↗
27. ATP-DenseNet: a hybrid deep learning-based gender identification of handwriting10.1007/s00521-020-05237-3 ↗
28. HDRANet: hybrid dilated residual attention network for SAR image despeckling10.3390/rs11242921 ↗
29. ResNeSt: split-attention networks
30. Focal loss for dense object detection
31. Two-branch deep neural network for underwater image enhancement in HSV color space10.1109/LSP.2021.3099746 ↗
32. Advanced ship detection and ocean monitoring with satellite imagery and deep learning for marine science applications