使用条件生成对抗网络生成船舶航迹特征

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

引用次数: 0

摘要

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。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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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来源期刊

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.