Robotics & Machine Learning Daily News2024,Issue(Nov.21) :66-67.

Researcher from China University of Mining and Technology Discusses Findings in Robotics (The application of Deep Learning in the field of Robotics)

中国矿业大学研究员机器人学发现(深度学习在机器人学中的应用机器人学领域

Robotics & Machine Learning Daily News2024,Issue(Nov.21) :66-67.

Researcher from China University of Mining and Technology Discusses Findings in Robotics (The application of Deep Learning in the field of Robotics)

中国矿业大学研究员机器人学发现(深度学习在机器人学中的应用机器人学领域

扫码查看

摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器人的研究发现在一份新的报告中被使用。根据新闻报道NewsRx编辑在中国米宁科技大学发表的研究报告称,"摘要"。我们的新闻编辑从中国矿业大学的研究中获得了一句话:深度学习作为近两年来发展迅速的一个新领域,受到了越来越多的关注研究人员的注意力。神经网络采用广泛互联结构和有效学习模拟人脑信息加工过程的机制是人脑信息加工的重要组成部分人工智能发展的方法。与浅层模型相比,深层学习可以通过增加层数,实现更强的无监督自主学习能力网络。在过去,机器人需要由人类控制;他们控制机器人完成不同的任务。近年来,研究人员试图将de ep学习应用于机器人领域。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on robotics are disc ussed in a new report. According to news reportingout of China University of Mi ning and Technology by NewsRx editors, research stated, “Abstract.”Our news editors obtained a quote from the research from China University of Min ing and Technology:“As a new field with rapid development in the past two decad es, deep learning has received more and moreattention from researchers. Neural network adopts widely interconnected structure and effective learningmechanisms to simulate the process of information processing in the human brain, which is an importantmethod in the development of artificial intelligence. Compared with shallow models, deep learning canachieve stronger unsupervised autonomous lear ning capabilities by increasing the number of layers of thenetwork. In the past , the robots needed to be controlled by the humans; they controlled the robot to finishdifferent tasks. In recent years, the researchers have tried to apply de ep learning in the field of robots.”

Key words

China University of Mining and Technolog y/Emerging Technologies/Machine Learning/Nano-robot/Robot/Robotics

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文