Generation of Vessel Track Characteristics Using a Conditional Generative Adversarial Network (CGAN)

IF 2.9 4区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Applied Artificial Intelligence Pub Date : 2024-05-31 DOI:10.1080/08839514.2024.2360283
Jessica N.A Campbell, Martha Dais Ferreira, Anthony W. Isenor
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Abstract

Machine learning (ML) models often require large volumes of data to learn a given task. However, access and existence of training data can be difficult to acquire due to privacy laws and availabili...
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使用条件生成对抗网络生成船舶航迹特征
机器学习(ML)模型通常需要大量数据来学习特定任务。然而,由于隐私法和可利用性等原因,训练数据的访问和存在可能很难获得。
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来源期刊
Applied Artificial Intelligence
Applied Artificial Intelligence 工程技术-工程:电子与电气
CiteScore
5.20
自引率
3.60%
发文量
106
审稿时长
6 months
期刊介绍: Applied Artificial Intelligence addresses concerns in applied research and applications of artificial intelligence (AI). The journal also acts as a medium for exchanging ideas and thoughts about impacts of AI research. Articles highlight advances in uses of AI systems for solving tasks in management, industry, engineering, administration, and education; evaluations of existing AI systems and tools, emphasizing comparative studies and user experiences; and the economic, social, and cultural impacts of AI. Papers on key applications, highlighting methods, time schedules, person-months needed, and other relevant material are welcome.
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