|
|
|
|
|
Haoran Liu, Kehui Xu, Bin Li, Ya Han and Guandong Li
Machine learning classifiers have been rarely used for the identification of seafloor sediment types in the rapidly changing dredge pits for coastal restoration. Our study uses multiple machine learning classifiers to identify the sediment types of the C...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chenhong Yan, Shefeng Yan, Tianyi Yao, Yang Yu, Guang Pan, Lu Liu, Mou Wang and Jisheng Bai
Ship-radiated noise classification is critical in ocean acoustics. Recently, the feature extraction method combined with time?frequency spectrograms and convolutional neural networks (CNNs) has effectively described the differences between various underw...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shih-Hsien Hsu, Fu-Ming Tzu, Yi-Dong Chen and Chun-Wei Huang
This paper addresses the growing concern over air pollutant emissions (NOx, SOx, PM, CO2) from ocean-going vessels in harbor areas and the role of Onshore Power Supply (OPS) systems in mitigating these emissions during vessel berthing. However, the slow ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Mostafa Hamdy Salem, Yujian Li, Zhaoying Liu and Ahmed M. AbdelTawab
Deep learning has been used to improve intelligent transportation systems (ITS) by classifying ship targets in interior waterways. Researchers have created numerous classification methods, but they have low accuracy and misclassify other ship targets. As...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiawen Li, Yun Yang, Xin Li, Jiahua Sun and Ronghui Li
Vessel monitoring technology involves the application of remote sensing technologies to detect and identify vessels in various environments, which is critical for monitoring vessel traffic, identifying potential threats, and facilitating maritime safety ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Miro Petkovic, Igor Vujovic, Zvonimir Lu?ic and Jo?ko ?oda
Automated surveillance systems based on machine learning and computer vision constantly evolve to improve shipping and assist port authorities. The data obtained can be used for port and port property surveillance, traffic density analysis, maritime safe...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chang Liu, Shize Zhang, Lufang Cao and Bin Lin
Automatic identification system (AIS) data record a ship?s position, speed over ground (SOG), course over ground (COG), and other behavioral attributes at specific time intervals during a ship?s voyage. At present, there are few studies in the literature...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shuang Yang, Lingzhi Xue, Xi Hong and Xiangyang Zeng
Recently, deep learning has been widely used in ship-radiated noise classification. To improve classification efficiency, avoiding high computational costs is an important research direction in ship-radiated noise classification. We propose a lightweight...
ver más
|
|
|
|
|
|
|
|
|
|
|
Sivapriya Sethu Ramasubiramanian, Suresh Sivasubramaniyan and Mohamed Fathimal Peer Mohamed
Detection and classification of icebergs and ships in synthetic aperture radar (SAR) images play a vital role in marine surveillance systems even though available adaptive threshold methods give satisfying results on detection and classification for ship...
ver más
|
|
|
|
|
|
|
|
|
|
|
Paolo Massimo Buscema, Giulia Massini, Giovanbattista Raimondi, Giuseppe Caporaso, Marco Breda and Riccardo Petritoli
The automatic identification system (AIS) facilitates the monitoring of ship movements and provides essential input parameters for traffic safety. Previous studies have employed AIS data to detect behavioral anomalies and classify vessel types using supe...
ver más
|
|
|
|
|
|