Ensemble learning for image recognition

Xu Chen, Long Hong, Guofang Huang
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引用次数: 1

Abstract

With the continuous development of the Internet and information technology, data has penetrated into every area of today's industry and business functions. Now, data has been already one of the most valuable assets in the Internet and a core element of a company's competitiveness. There seems to have endless data on the Internet, then most of it cannot create value. When we face data mining, wo need to complete a lot of data cleaning tasks. Nowadays, the rapid development of machine learning, especially the deep of learning, has made excellent achievements in natural language processing and image recognition. The paper combines multiple strong learning machine to complete the data learning tasks and image recognition based on ensemble learning, thereby reduce the pressure on the server storage and investment of resource.
图像识别的集成学习
随着互联网和信息技术的不断发展,数据已经渗透到当今工业和商业功能的各个领域。现在,数据已经是互联网上最有价值的资产之一,也是公司竞争力的核心要素。互联网上似乎有无穷无尽的数据,但其中大部分无法创造价值。当我们面对数据挖掘时,我们需要完成大量的数据清理任务。如今,机器学习特别是深度学习的迅猛发展,在自然语言处理和图像识别方面取得了优异的成绩。本文结合多个强学习机来完成基于集成学习的数据学习任务和图像识别,从而减少了服务器存储的压力和资源的投入。
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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