# A Ship Detection Model Based on Dynamic Convolution and an Adaptive Fusion Network for Complex Maritime Conditions

## TL;DR

This paper introduces YOLO-Vessel, a ship detection model that improves accuracy and real-time performance in complex maritime conditions.

## Contribution

The paper proposes YOLO-Vessel with ELAN-ODConv, space-to-depth structure, and ASFFPredict for better ship detection in complex environments.

## Key findings

- YOLO-Vessel achieves 78.3% mean average precision, outperforming YOLOv7 and Faster R-CNN.
- The model maintains real-time detection at 8.0 ms/frame, suitable for maritime applications.
- YOLO-Vessel shows superior performance in adverse weather conditions for ship detection.

## Abstract

Ship detection is vital for maritime safety and vessel monitoring, but challenges like false and missed detections persist, particularly in complex backgrounds, multiple scales, and adverse weather conditions. This paper presents YOLO-Vessel, a ship detection model built upon YOLOv7, which incorporates several innovations to improve its performance. First, we devised a novel backbone network structure called Efficient Layer Aggregation Networks and Omni-Dimensional Dynamic Convolution (ELAN-ODConv). This architecture effectively addresses the complex background interference commonly encountered in maritime ship images, thereby improving the model’s feature extraction capabilities. Additionally, we introduce the space-to-depth structure in the head network, which can solve the problem of small ship targets in images that are difficult to detect. Furthermore, we introduced ASFFPredict, a predictive network structure addressing scale variation among ship types, bolstering multiscale ship target detection. Experimental results demonstrate YOLO-Vessel’s effectiveness, achieving a 78.3% mean average precision (mAP), surpassing YOLOv7 by 2.3% and Faster R-CNN by 11.6%. It maintains real-time detection at 8.0 ms/frame, meeting real-time ship detection needs. Evaluation in adverse weather conditions confirms YOLO-Vessel’s superiority in ship detection, offering a robust solution to maritime challenges and enhancing marine safety and vessel monitoring.