Underwater shipwreck identification technology, as a crucial technique in the field of marine surveying, plays a significant role in areas such as the search and rescue of maritime disaster shipwrecks. When facing the...Underwater shipwreck identification technology, as a crucial technique in the field of marine surveying, plays a significant role in areas such as the search and rescue of maritime disaster shipwrecks. When facing the task of object detection in shipwreck side-scan sonar images, due to the complex seabed environment, it is difficult to extract object features, often leading to missed detections of shipwreck images and slow detection speed. To address these issues, this paper proposes an object detection algorithm, CSC-YOLO (Context Guided Block, Shared Conv_Group Normalization Detection, Cross Stage Partial with 2 Partial Convolution-You Only Look Once), based on YOLOv8n for shipwreck side-scan sonar images. Firstly, to tackle the problem of small samples in shipwreck side-scan sonar images, a new dataset was constructed through offline data augmentation to expand data and intuitively enhance sample diversity, with the Mosaic algorithm integrated to strengthen the network’s generalization to the dataset. Subsequently, the Context Guided Block (CGB) module was introduced into the backbone network model to enhance the network’s ability to learn and express image features. Additionally, by employing Group Normalization (GN) techniques and shared convolution operations, we constructed the Shared Conv_GN Detection (SCGD) head, which improves the localization and classification performance of the detection head while significantly reducing the number of parameters and computational load. Finally, the Partial Convolution (PConv) was introduced and the Cross Stage Partial with 2 PConv (C2PC) module was constructed to help the network maintain effective extraction of spatial features while reducing computational complexity. The improved CSC-YOLO model, compared with the YOLOv8n model on the validation set, mean Average Precision (mAP) increases by 3.1%, Recall (R) increases by 6.4%, and the F1-measure (F1) increases by 4.7%. Furthermore, in the improved algorithm, the number of parameters decreases by 20%, the computational complexity decreases by 23.2%, and Frames Per Second (FPS) increases by 17.6%. In addition, compared with the advanced popular model, the superiority of the proposed model is proved. The subsequent experiments on real side-scan sonar images of shipwrecks fully demonstrate that the CSC-YOLO algorithm meets the requirements for actual side-scan sonar detection of underwater shipwrecks.展开更多
Shipwreck salvage is a risky,time-consuming,and expensive process.Although there are many sunken ships along coastlines and in the open seas,the salvage process of a sunken ship has rarely been reported.The integrated...Shipwreck salvage is a risky,time-consuming,and expensive process.Although there are many sunken ships along coastlines and in the open seas,the salvage process of a sunken ship has rarely been reported.The integrated salvage of the"Yangtze River EstuaryⅡ"shipwreck used a novel method with 22 closely locked curved rectangular pipes to form a watertight base that wrapped the shipwreck inside.The basing was lifted out of the water using a powerful crane situated on an engineering ship.For the first time,the tunneling method was used in a shipwreck salvage project,significantly reducing the disturbance to the shipwreck and its stowage,thereby preserving the original state and integrity of the shipwreck to the greatest extent.In this study,the basic concepts of the salvage method and process are explained.Solutions to critical issues in the new salvage method are provided,including jacking force prediction and major considerations for the structural design of the salvage system.The design of the salvage system and salvage process of the"Yangtze River EstuaryⅡ"shipwreck are introduced.The monitored jacking force,pipe deformation,and observed water-tightness verified that the proposed method was effective and efficient.Other possible application scenarios for the proposed method are presented at the end.展开更多
The 2025 exploration of the famous Antikythera shipwreck brought significant new findings.It offers us a look into the ancient ship building,trade and sea life in the Mediterranean region.
Changsha has played a pioneering role in reshaping cross-continental trade and cooperation.From the 50,000 pieces of Changsha Kiln ceramics recovered from the Tang Dynasty shipwreck“Black Stone”to today’s weekly ca...Changsha has played a pioneering role in reshaping cross-continental trade and cooperation.From the 50,000 pieces of Changsha Kiln ceramics recovered from the Tang Dynasty shipwreck“Black Stone”to today’s weekly cargo flights between China and Africa,Changsha’s trade with the African continent has spanned over a thousand years.This historic cultural city is playing an increasingly vital role in China-Africa economic and trade cooperation,with a spirit of innovation and openness.展开更多
基金supported in part by the Hainan Provincial Natural Science Foundation(Grant No.420CXTD439)Sanya Science and Technology Special Fund(Grant No.2022KJCX83)+1 种基金Institute and Local Cooperation Foundation of Sanya in China(Grant No.2019YD08)National Natural Science Foundation of China(Grant No.61661038).
文摘Underwater shipwreck identification technology, as a crucial technique in the field of marine surveying, plays a significant role in areas such as the search and rescue of maritime disaster shipwrecks. When facing the task of object detection in shipwreck side-scan sonar images, due to the complex seabed environment, it is difficult to extract object features, often leading to missed detections of shipwreck images and slow detection speed. To address these issues, this paper proposes an object detection algorithm, CSC-YOLO (Context Guided Block, Shared Conv_Group Normalization Detection, Cross Stage Partial with 2 Partial Convolution-You Only Look Once), based on YOLOv8n for shipwreck side-scan sonar images. Firstly, to tackle the problem of small samples in shipwreck side-scan sonar images, a new dataset was constructed through offline data augmentation to expand data and intuitively enhance sample diversity, with the Mosaic algorithm integrated to strengthen the network’s generalization to the dataset. Subsequently, the Context Guided Block (CGB) module was introduced into the backbone network model to enhance the network’s ability to learn and express image features. Additionally, by employing Group Normalization (GN) techniques and shared convolution operations, we constructed the Shared Conv_GN Detection (SCGD) head, which improves the localization and classification performance of the detection head while significantly reducing the number of parameters and computational load. Finally, the Partial Convolution (PConv) was introduced and the Cross Stage Partial with 2 PConv (C2PC) module was constructed to help the network maintain effective extraction of spatial features while reducing computational complexity. The improved CSC-YOLO model, compared with the YOLOv8n model on the validation set, mean Average Precision (mAP) increases by 3.1%, Recall (R) increases by 6.4%, and the F1-measure (F1) increases by 4.7%. Furthermore, in the improved algorithm, the number of parameters decreases by 20%, the computational complexity decreases by 23.2%, and Frames Per Second (FPS) increases by 17.6%. In addition, compared with the advanced popular model, the superiority of the proposed model is proved. The subsequent experiments on real side-scan sonar images of shipwrecks fully demonstrate that the CSC-YOLO algorithm meets the requirements for actual side-scan sonar detection of underwater shipwrecks.
基金supported by Science and Technology Innovation Action Plan(Grant Nos.21DZ1201103 and 21DZ1201104)the National Natural Science Foundation of China(Grant No.52278407).
文摘Shipwreck salvage is a risky,time-consuming,and expensive process.Although there are many sunken ships along coastlines and in the open seas,the salvage process of a sunken ship has rarely been reported.The integrated salvage of the"Yangtze River EstuaryⅡ"shipwreck used a novel method with 22 closely locked curved rectangular pipes to form a watertight base that wrapped the shipwreck inside.The basing was lifted out of the water using a powerful crane situated on an engineering ship.For the first time,the tunneling method was used in a shipwreck salvage project,significantly reducing the disturbance to the shipwreck and its stowage,thereby preserving the original state and integrity of the shipwreck to the greatest extent.In this study,the basic concepts of the salvage method and process are explained.Solutions to critical issues in the new salvage method are provided,including jacking force prediction and major considerations for the structural design of the salvage system.The design of the salvage system and salvage process of the"Yangtze River EstuaryⅡ"shipwreck are introduced.The monitored jacking force,pipe deformation,and observed water-tightness verified that the proposed method was effective and efficient.Other possible application scenarios for the proposed method are presented at the end.
文摘The 2025 exploration of the famous Antikythera shipwreck brought significant new findings.It offers us a look into the ancient ship building,trade and sea life in the Mediterranean region.
文摘Changsha has played a pioneering role in reshaping cross-continental trade and cooperation.From the 50,000 pieces of Changsha Kiln ceramics recovered from the Tang Dynasty shipwreck“Black Stone”to today’s weekly cargo flights between China and Africa,Changsha’s trade with the African continent has spanned over a thousand years.This historic cultural city is playing an increasingly vital role in China-Africa economic and trade cooperation,with a spirit of innovation and openness.
