从感知器到深度神经网络

P. Lacko
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引用次数: 2

摘要

深度神经网络是人工智能研究的热点领域。谷歌、微软、百度和脸书等大公司都在支持这一领域的研发。最近在围棋比赛中战胜人类棋手表明了这种方法的巨大潜力。基于深度学习技术的机器学习方法比基于人工调整不同领域特征的现有方法带来了显着的增益。在本文中,我们介绍了深度神经网络从最初的神经元模型到今天的深度架构的演变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
From perceptrons to deep neural networks
Deep neural networks are intensively researched field of artificial intelligence. Big companies like Google, Microsoft, Baidu or Facebook are supporting research and development in this field. The recent victory over human player in the game of Go points to a huge potential of this approach. Machine learning approaches based on deep learning techniques bring significant gain over existing methods based on manually tuned features in different areas. In this paper we present the evolution of deep neural networks from first neuron models towards today's deep architectures.
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