Knowledge Extraction for Automatic Driving Control by Using Local Correlation Features

2021 ◽  
Author(s):  
Jia Lv
Keyword(s):  
Knowledge Extraction ◽  
Local Correlation ◽  
Automatic Driving

Detection of the Structural Failing Point Using Correlation and Local Correlation Analysis

2020 ◽  
Author(s):  
Hyounkyun Oh ◽  
Younghan Jung ◽  
Junyong Ahn ◽  
Sujin Kim ◽  
M. Myung Jeong
Keyword(s):  
Correlation Analysis ◽  
Local Correlation

Auto Markets in the World and Strategy of Japan’s Companies

2019 ◽  
Vol 10 (10) ◽  
pp. 1003-1008
Author(s):  
Hiroyuki Matsuoka ◽  
Keyword(s):  
Saudi Arabia ◽  
Electric Vehicle ◽  
New Technologies ◽  
Auto Industry ◽  
Domestic Market ◽  
Automatic Driving ◽  
The World ◽  
Almost All ◽  
Made In

In the world auto market, top three companies are VW(Volkswagen), Runault-Nissan-Mistubishi, and Toyota. About some selected countries and areas, China, England, Italy, Australia, Germany, Turkey, Russia, Sweden, USA, Brazil, UAE, Japan, Vietnam and Thailand are more competitive. However, the situation is different. Seeing monopolistic market countries and areas, Saudi Arabia, Taiwan, Korea, Malaysia, France, India, and Pakistan, in particular, the influence of Japan to Taiwan, India, and Pakistan is very big. But in Korea and France, their own companies’ brands occupy the market. In Japan domestic market, the overall situation is competitive. Almost all vehicles made in Japan are Japanese brand. From now on, we have to note the development of electric vehicle (EV) and other new technologies such as automatic driving and connected car. That is because they will give a great impact on the auto industry and market of Japan. Now Japan’s auto industry is going to be consolidated into three groups, Honda, Toyota group, and Renault-Nissan-Mitsubishi group for seeking the scale merit of economy. Therefore, I will pay attention to the worldwide development of EV and other new technologies and the reorganization of auto companies groups.

A Multi-Language System For Knowledge Extraction In E-Learning Videos

2006 ◽  
Vol 3 (1) ◽  
pp. 48-55
Author(s):  
Aparesh Sood ◽  
◽  
Ankush Mittal ◽  
Divya Sarthi ◽  
◽  
...  
Keyword(s):  
Knowledge Extraction ◽  
Language System ◽  
E Learning

scholarly journals Context-Aware Holographic Communication Based on Semantic Knowledge Extraction

2021 ◽  
Author(s):  
Agata Manolova ◽  
Krasimir Tonchev ◽  
Vladimir Poulkov ◽  
Sudhir Dixir ◽  
Peter Lindgren
Keyword(s):  
Deep Neural Networks ◽  
Data Gathering ◽  
Communication Technologies ◽  
Knowledge Extraction ◽  
Semantic Knowledge ◽  
Business Model Innovation ◽  
Context Aware ◽  
Human Body Model ◽  
Network Resource ◽  
Body Model

AbstractAugmented, mixed and virtual reality are changing the way people interact and communicate. Five dimensional communications and services, integrating information from all human senses are expected to emerge, together with holographic communications (HC), providing a truly immersive experience. HC presents a lot of challenges in terms of data gathering and transmission, demanding Artificial Intelligence empowered communication technologies such as 5G. The goal of the paper is to present a model of a context-aware holographic architecture for real time communication based on semantic knowledge extraction. This architecture will require analyzing, combining and developing methods and algorithms for: 3D human body model acquisition; semantic knowledge extraction with deep neural networks to predict human behaviour; analysis of biometric modalities; context-aware optimization of network resource allocation for the purpose of creating a multi-party, from-capturing-to-rendering HC framework. We illustrate its practical deployment in a scenario that can open new opportunities in user experience and business model innovation.

The Multi-sensor Fusion Automatic Driving Test Scene Algorithm based on Cloud Platform

2020 ◽  
Author(s):  
Yanbo Liu ◽  
Liangren Shi ◽  
Wenchao Xu ◽  
Xin Xiong ◽  
Weiqi Sun ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Cloud Platform ◽  
Automatic Driving
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