GDB‐YOLOv5s: Improved YOLO‐based Model for Ship Detection in SAR Images In recent years, deep learning methods were good solutions for object detection in synthetic aperture radar (SAR) images. However, the problems of complex ... D Chen,R Ju,C Tu,... - 《Iet Image Processing》 被引...
Objectives A lightweight remote sensing ship target detection algorithm LR-YOLO based on improved YOLOv5s is proposed to meet the requirements of lightweight and fast inference in ship target detection tasks in remote sensing images. Methods Firstly, the backbone network adopts ShuffleNet v2 Block ...
To improve the real-time performance of target detection in SAR images, based on the YOLOv2 model architecture, ref. [45] developed a new network architecture with fewer layers, namely YOLOv2-reduced. Its detection performance is similar to YOLOv2, but there is a significant improvement in ...
However, for accuracy, the two-stage detectors are better than that of one-stage, especially for small dense object detection. For SAR ship detection, Deep CNNs have been widely applied in recent years. As a typical one-stage detection method, YOLOv2 was utilized to detect ships in SAR ...
In the field of object recognition, the detection methods based on CNN can be classified into two categories (1): single-stage detectors such as SDD, Yolov1/v2v3/v4, and RetinaNet; and (2) two-stage detectors such as R-CNN, Fast R-CNN, Faster R-CNN, and Mask-RCNN. Although they...
Ship detection in SAR image using YOLOv2. In Proceedings of the 37th Chinese Control Conference (CCC 2018), Wuhan, China, 25–27 July 2018; pp. 9495–9499. [Google Scholar] Zénere, M.P. SAR Image Quality Assessment; Universidad Nacional de Córdoba: Córdoba, Argentina, 2012. [Google ...
The monitoring of worldwide ship traffic is a field of high topicality. Activities like piracy, ocean dumping, and refugee transportation are in the news every day. The detection of ships in remotely sensed data from airplanes, drones, or spacecraft cont
Furthermore, HTC [24] combined Cascade R-CNN and Mask R-CNN to leverage relationships between detection and segmentation, offering the state-of-the-art performance [37,38]. Therefore, we select it as our experimental baseline. 2.2. SAR Ship Instance Segmentation Recently, many scholars in the...
To solve this problem, in this paper, we propose a few-shot multi-class ship detection algorithm with attention feature map and multi-relation detector (AFMR) for remote sensing images. We use the basic framework of You Only Look Once (YOLO), and use the attention feature map module to ...
SAR raw data processing; ship detection; convolutional neural networks1. Introduction Since the deployment of the first satellite with a synthetic aperture remote sensing system into orbit in 1978 [1], the use of SAR imagery has been a vital part of several scientific domains, including ...