Joint Detection Method of ASW Systems of System Based on ASDP Area of Probability

2012 ◽  
Author(s):  
Wu Xiaoyong ◽  
Liu Lin ◽  
Zhong Weijun
Keyword(s):  
Detection Method ◽  
Joint Detection

scholarly journals Pedestrian and cyclist detection based on deep neural network fast R-CNN

2019 ◽  
Vol 16 (2) ◽  
pp. 172988141982965 ◽  
Author(s):  
Kelong Wang ◽  
Wei Zhou
Keyword(s):  
Neural Network ◽  
Target Detection ◽  
Deep Neural Network ◽  
Detection Method ◽  
Feature Fusion ◽  
Intelligent Vehicles ◽  
Urban Traffic ◽  
Joint Detection ◽  
Difficult Case ◽  
Important Basis

In this article, a unified joint detection framework for pedestrian and cyclist is established to realize the joint detection of pedestrian and cyclist targets. Based on the target detection of fast regional convolution neural network, a deep neural network model suitable for pedestrian and cyclist detection is established. Experiments for poor detection results for small-sized targets and complex and changeable background environment; various network improvement schemes such as difficult case extraction, multilayer feature fusion, and multitarget candidate region input were designed to improve detection and to solve the problems of frequent false detections and missed detections in pedestrian and cyclist target detection. Results of experimental verification of the pedestrian and cyclist database established in Beijing’s urban traffic environment showed that the proposed joint detection method for pedestrians and cyclists can realize the stable tracking of joint detection and clearly distinguish different target categories. Therefore, an important basis for the behavior decision of intelligent vehicles is provided.

Application of On-Line Ultrasonic and UHF Partial Discharge Detection in 1000kV GIS

2014 ◽  
Vol 644-650 ◽  
pp. 3480-3484 ◽  
Author(s):  
Fuan Chen ◽  
Hui Zeng Tang ◽  
Hong Gang Li
Keyword(s):  
High Voltage ◽  
High Frequency ◽  
Detection Method ◽  
Ultrasonic Method ◽  
Partial Discharge ◽  
Joint Detection ◽  
Frequency Method ◽  
Advantages And Disadvantages ◽  
On Line ◽  
Discharge Detection

This paper introduces the detecting principle、range of application and interferencerejection of Ultrasonic And UHF Partial Discharge Detection In GIS(Gas Insulated Switchgear).In view of the advantages and disadvantages of ultrasonic and UHF detection,this paper proposesa quick joint detection method, which uses UHF (Ultra High Frequency) method to online detectthe suspected discharge range in real time, adopts ultrasonic method to determine the specificdischarge points, finally through a concrete instance in a 1000KV UHV(Ultra High Voltage)Substation verified the feasibility of the joint detection method.

scholarly journals A Novel Flickering Multi-Target Joint Detection Method Based on a Biological Memory Model

2021 ◽  
Vol 14 (1) ◽  
pp. 39
Author(s):  
Qian Zhang ◽  
Weibo Huo ◽  
Jifang Pei ◽  
Yongchao Zhang ◽  
Jianyu Yang ◽  
...  
Keyword(s):  
Target Detection ◽  
Detection Method ◽  
Detection Performance ◽  
Detection Methods ◽  
Memory Model ◽  
Joint Detection ◽  
Radar Images ◽  
Biological Memory ◽  
Threshold Criterion ◽  
Target States

The robust target detection ability of marine navigation radars is essential for safe shipping. However, time-varying river and sea surfaces will induce target scattering changes, known as fluctuating characteristics. Moreover, the targets exhibiting stronger fluctuation disappear in some frames of the radar images, which is known as flickering characteristics. This phenomenon causes a severe decline in the detection performance of traditional detection methods. A biological memory model-based dynamic programming multi-target joint detection method was proposed to address this issue in this paper. Firstly, a global detection operator is used to discretize the multi-target state into multiple single-target states, achieving the discretization of numerous targets. Meanwhile, updating the formula of the memory weight merit function can strengthen the joint frame correlation of the flickering characteristics target. The progressive loop integral is utilized to update the target states to optimize the candidate target set. Finally, a two-stage threshold criterion is utilized to detect the target at different amplitude levels accurately. Simulation and experimental results are given to validate the assertion that the detection performance of the proposed method is greatly improved under a low SCR of 3-8 dB for multiple flickering target detection.

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