Ship detection on synthetic aperture radar (SAR) imagery has many valuable applications for both civil and military fields and has received extraordinary attention in recent years. The traditional detection met
This study aims to address the unreasonable assignment of positive and negative samples and poor localization quality in ship detection in complex scenes. Therefore, in this study, a Synthetic Aperture Radar (SAR) ship detection network (A3-IO
This study adheres to a set of guidelines for performing an SLR. The mission of the SLR is to find publications, publishers, deep learning types, improved and amended deep learning techniques, impacts, proactive approaches, key parameters, and applications in ship detection by SAR images, as we...
Lightweight ship detection offers the dual benefits of rapid detection and low computational cost, making it particularly advantageous for inland waterway
We propose a lightweight ship object detection method based on feature enhancement called YOLO-Ships, which effectively solves problems, such as the insufficient memory of large models and the unsuitability of the current models for deployment in embedded system equipment. The YOLO-Ships model ...
(WGAN-GP) is first utilized in this study to generate sufficient informative small ship images as the additional training samples for training data enhancement, and an improved YOLO v2 algorithm is then applied to complete the task of small ship detection based on the augmented training samples (...
Ship detection plays a pivotal role in efficient marine monitoring, port management, and safe navigation. However, the development of ship detection techni
In general, it has excellent performance in polyp detection. The target detection method in SAR ship detec- tion has also become a very prevalent study point. Scholars, such as Zhang et al. [53] proposed an improved Faster- RCNN method in the literature. The method could improve the ...
Compared with other excellent object detection models, YOLO-SD still has an edge in terms of overall performance. Keywords: synthetic aperture radar (SAR); small ship detection; deep learning; YOLOX Graphical Abstract1. Introduction The imaging effect of traditional optical sensing is always affected...
Proposed a CNN model, NST-YOLO11, integrating Neural Swin Transformer (Neural Swin-T) and Cross-Stage connection Spatial Pyramid Pooling-Fast (CS-SPPF) based on YOLO11; 3. Summarized the performance of the proposed model for arbitrary-oriented ship detection in SAR images on RSDD-SAR and SSD...