一种基于车联网的神经智能系统方案

M. Sasaki
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引用次数: 0

摘要

基于近年来自动驾驶汽车和网联汽车的技术趋势,我们提出了新的应用概念neuroits,它具有多视点跟踪、人的外观预测和集体智能三大技术特征。特别是通过将集体智能与传感控制相结合,我们将大大减少传统机器学习的严重瓶颈——大量GT (ground truth)的收集和教学的繁重任务。它还将大大提高超越感知的环境理解性能。本文以集体智慧为研究对象,探讨了估计真值(ET)向估计真值演进过程中的技术实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A proposal for Neuro-ITS over the connected vehicles network
On the basis of the recent technical trend of automated vehicles and connected vehicles, we have been proposing the new application concept Neuro-ITS which has three major technical features such as multi-viewpoint tracking, human appearance prediction, and collective intelligence. Especially by combining the collective intelligence with sensing control, we will drastically reduce the hectic tasks to collect and teach huge size of GT (ground truth) which has been serious bottleneck of conventional machine learning. Also it will greatly improve the performance of environment understanding beyond perception. In this article, we focus on the collective intelligence and investigate the technical realization regarding the evolutionary process of ET (estimated truth) towards GT.
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