AI处理器中的学习

IF 1.7 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE ADCAIJ-Advances in Distributed Computing and Artificial Intelligence Journal Pub Date : 2021-11-02 DOI:10.30564/aia.v3i2.3878
Xinhua Wang, Weikang Wu
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引用次数: 0

摘要

可以运行人工智能算法的AI处理器,本质上是在各种应用中执行特殊算法的最先进的加速器。特别是,这四个人工智能应用:VR/AR智能手机游戏、高性能计算、高级驾驶辅助系统和物联网。使用卷积神经网络(cnn)的深度学习涉及将智能嵌入到应用程序中以执行任务,并且达到了前所未有的精度。通常,强大的多核处理器和片上张量处理加速单元是深度学习AI处理器的突出硬件特征。传感器采集数据后,采用图像处理技术、语音识别、无人机自主导航等工具对数据进行预处理和分析。近年来,认知频谱感知、计算机视觉、语义推理等与深度学习相关的技术成为当前研究的热点。
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Learning in AI Processor
AI processor, which can run artificial intelligence algorithms, is a state-of-the-art accelerator,in essence, to perform special algorithm in various applications. In particular,these are four AI applications: VR/AR smartphone games, high-performance computing, Advanced Driver Assistance Systems and IoT. Deep learning using convolutional neural networks (CNNs) involves embedding intelligence into applications to perform tasks and has achieved unprecedented accuracy [1]. Usually, the powerful multi-core processors and the on-chip tensor processing accelerator unit are prominent hardware features of deep learning AI processor. After data is collected by sensors, tools such as image processing technique, voice recognition and autonomous drone navigation, are adopted to pre-process and analyze data. In recent years, plenty of technologies associating with deep learning Al processor including cognitive spectrum sensing, computer vision and semantic reasoning become a focus in current research.
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
22
审稿时长
4 weeks
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