Ship-YOLOv5:Ship Target Detection Based on Enhanced Feature Fusion

Author:

Zhang Yu1ORCID,Li Wenqiang1ORCID,Guo Pengcheng1ORCID,Liu Jiabing1ORCID,Hu Qing1ORCID

Affiliation:

1. College of Information Science and Technology, Dalian Maritime University, China

Funder

the national key research and development plan

science and technology plan of liaoning province

Cultivation Program for the Excellent Doctoral Dissertation of Dalian Maritime University

Publisher

ACM

Reference16 articles.

1. Khmag, A., Al-Haddad, S.A.R., Ramli, A.R. et al.: Single image dehazing using second-generation wavelet transforms and the mean vector L2-norm. Vis Comput 34, 675–688 (2018) Yao Tingting, Zhang Bo, and Liu Xiaoming. Feature Enhanced Fully Convolutional Network for Ship Detection[J].Journal of computer-Aided Design & Computer Graphics, 2022, 34(07): 1028-1036.

2. A Lightweight Faster R-CNN for Ship Detection in SAR Images

3. Small Ship Detection of SAR Images Based on Optimized Feature Pyramid and Sample Augmentation

4. Aeroengine Blade Surface Defect Detection System Based on Improved Faster RCNN

5. MAM Faster R-CNN: Improved Faster R-CNN based on Malformed Attention Module for object detection on X-ray security inspection

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