Automatic detection technique of preceding lane and vehicle

2008 ◽  
Author(s):  
Banggui Zheng ◽  
Bingxiang Tian ◽  
Jianmin Duan ◽  
Dezhi Gao
Keyword(s):  
Automatic Detection ◽  
Detection Technique

Enhancement of Defect Detectability in Pneumatic Pressure Equipment Using an Automatic Detection Technique in ECPT

2020 ◽  
Vol 49 (1) ◽  
pp. 20180724
Author(s):  
Bo Zhang ◽  
YuHua Cheng ◽  
Chun Yin ◽  
Xuegang Huang ◽  
Sara Dadras ◽  
...  
Keyword(s):  
Automatic Detection ◽  
Detection Technique ◽  
Pneumatic Pressure ◽  
Defect Detectability

High sensitive automatic detection technique for space objects

2020 ◽  
Vol 49 (5) ◽  
pp. 20201008
Author(s):  
张俊 Jun Zhang ◽  
张洪健 Hongjian Zhang ◽  
孙大开 Dakai Sun ◽  
王立 Li Wang ◽  
武延鹏 Yanpeng Wu ◽  
...  
Keyword(s):  
Automatic Detection ◽  
Detection Technique ◽  
Space Objects

Automatic Detection of Semantic Clusters in Glossaries

2021 ◽  
pp. 711-727
Author(s):  
Marcela Ridao ◽  
Jorge Horacio Doorn
Keyword(s):  
Natural Language ◽  
Business Process ◽  
Directed Graphs ◽  
Automatic Detection ◽  
Cluster Detection ◽  
Important Task ◽  
Detection Technique ◽  
Software System ◽  
Visualization Technique ◽  
Hidden Information

To define the services that a software system will provide, in terms of the business process needs, is a rather important task. As a first step, the requirements engineer must deeply understand the peculiarities of the context in which the future software system will run. There have been proposed several approaches to elicit and model such knowledge. The research whose main results are presented in this chapter, was carried out in a process that models all the information acquired in natural language. The advantages of the use of natural language are somehow shadowed by its ambiguity and the way models are arranged. This chapter deals with some techniques developed to visualize hidden information in this sort of models. This is mainly done by means of the use of directed graphs and the finding of clusters on them. This chapter enhances a previous one, by improving the visualization technique and by adding an automatic cluster detection technique.

The automatic detection of unattended social category information from unfamiliar faces

2014 ◽  
Author(s):  
Douglas Martin ◽  
Rachel Swainson ◽  
Gillian Slessor ◽  
Jacqui Hutchison ◽  
Diana Marosi
Keyword(s):  
Automatic Detection ◽  
Social Category ◽  
Category Information ◽  
Unfamiliar Faces
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