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CTDR-Net: Channel-Time Dense Residual Network for Detecting Crew Overboard Behavior

التفاصيل البيبلوغرافية
العنوان: CTDR-Net: Channel-Time Dense Residual Network for Detecting Crew Overboard Behavior
المؤلفون: Zhengbao Li, Jie Gao, Kai Ma, Zewei Wu, Libin Du
المصدر: Applied Sciences, Vol 14, Iss 3, p 986 (2024)
بيانات النشر: MDPI AG, 2024.
سنة النشر: 2024
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: crew overboard, CTDR-Net, DR-Net, CTAM, good balance, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: The efficient detection of crew overboard behavior has become an important element in enhancing the ability to respond to marine disasters. It remains challenging due to (1) the lack of effective features making feature extraction difficult and recognition accuracy low and (2) the insufficient computing power resulting in the poor real-time performance of existing algorithms. In this paper, we propose a Channel-Time Dense Residual Network (CTDR-Net) for detecting crew overboard behavior, including a Dense Residual Network (DR-Net) and a Channel-Time Attention Mechanism (CTAM). The DR-Net is proposed to extract features, which employs the convolutional splitting method to improve the extraction ability of sparse features and reduce the number of network parameters. The CTAM is used to enhance the expression ability of channel feature information, and can increase the accuracy of behavior detection more effectively. We use the LeakyReLU activation function to improve the nonlinear modeling ability of the network, which can further enhance the network’s generalization ability. The experiments show that our method has an accuracy of 96.9%, striking a good balance between accuracy and real-time performance.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/14/3/986; https://doaj.org/toc/2076-3417
DOI: 10.3390/app14030986
URL الوصول: https://doaj.org/article/71e2b2c4dd654effb6bad67372e066ca
رقم الأكسشن: edsdoj.71e2b2c4dd654effb6bad67372e066ca
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app14030986