中移(杭州)信息技术有限公司/中国移动杭州研发中心
Published:2017
移动端阅览
[1]郦荣.基于人工智能技术的富媒体信息管控研究[J].电信工程技术与标准化,2017,30(08):1-6.
郦荣. Artificial intelligence based rich media information monitor schemes[J]. 2017, 30(8): 1-6.
[1]郦荣.基于人工智能技术的富媒体信息管控研究[J].电信工程技术与标准化,2017,30(08):1-6. DOI: 10.13992/j.cnki.tetas.2017.08.001.
郦荣. Artificial intelligence based rich media information monitor schemes[J]. 2017, 30(8): 1-6. DOI: 10.13992/j.cnki.tetas.2017.08.001.
互联网时代
信息交流频繁
不良违法信息的传播也日趋严重。在此情况下
识别和过滤富媒体不良信息变得尤为重要。近年来
深度学习等人工智能技术的崛起极大地推动了图像识别领域的发展
相较于传统方法
深度学习的优势在于自动提取且具有更强大的表达能力。基于此
本文提出了一种基于深度学习的不良富媒体信息管控方案
达到净化互联网内容的目的。
In the internet era
as people communicating and data exchanging frequently
the spread of malicious information is becoming more and more serious. Therefore
it is particularly important to identify and filter spam(text
image
video) on the internet. In recent years
the appearance of deep learning has greatly pushed forward the frontier of computer vision research
and computer vision tasks like image classification and recognition have greatly benefited from it. Compared with traditional methods
the features automatically extracted by deep model have better representing power. In this paper
we propose a rich media information detection method based on the deep learning. As a result
it achieves the purpose of fi ltering internet content.
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