利用各种深度学习模型对基准数据集进行虚假内容检测

IF 1.4 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

International Journal of Computational Science and Engineering Pub Date : 2023-01-01 DOI:10.1504/ijcse.2023.10060449

Chetana Thaokar, Jitendra Kumar Rout, Himansu Das, Minakhi Rout

引用次数: 0

摘要

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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Fake content detection on benchmark dataset using various deep learning models

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来源期刊

International Journal of Computational Science and Engineering COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-

CiteScore

4.00

自引率

40.00%

发文量

期刊介绍： Computational science and engineering is an emerging and promising discipline in shaping future research and development activities in both academia and industry, in fields ranging from engineering, science, finance, and economics, to arts and humanities. New challenges arise in the modelling of complex systems, sophisticated algorithms, advanced scientific and engineering computing and associated (multidisciplinary) problem-solving environments. Because the solution of large and complex problems must cope with tight timing schedules, powerful algorithms and computational techniques, are inevitable. IJCSE addresses the state of the art of all aspects of computational science and engineering with emphasis on computational methods and techniques for science and engineering applications.