Two Brains, One Target: Design of a Multi-level Information Fusion Model Based on Dual-subject RSVP

2021 ◽  
pp. 109346
Author(s):  
Hangkui Zhang ◽  
Li Zhu ◽  
Senwei Xu ◽  
Jianting Cao ◽  
Wanzeng Kong
Keyword(s):  
Information Fusion ◽  
Fusion Model ◽  
Model Based ◽  
Level Information ◽  
Multi Level ◽  
Target Design

Application of multi-level information fusion for wear particle recognition of ferrographic images

2018 ◽  
Vol 26 (6) ◽  
pp. 1551-1560
Author(s):  
徐 斌 XU Bin ◽  
温广瑞 WEN Guang-rui ◽  
苏 宇 SU Yu ◽  
张志芬 ZHANG Zhi-fen ◽  
陈 峰 CHEN Feng ◽  
...  
Keyword(s):  
Information Fusion ◽  
Wear Particle ◽  
Particle Recognition ◽  
Level Information ◽  
Multi Level

Quantify: An Information Fusion Model Based on Syntactic and Semantic Analysis and Quality Assessments to Enhance Situation Awareness

2019 ◽  
pp. 563-586
Author(s):  
Leonardo Castro Botega ◽  
Allan Cesar Moreira de Oliveira ◽  
Valdir Amancio Pereira Junior ◽  
Jordan Ferreira Saran ◽  
Lucas Zanco Ladeira ◽  
...  
Keyword(s):  
Information Fusion ◽  
Situation Awareness ◽  
Semantic Analysis ◽  
Fusion Model ◽  
Model Based ◽  
Quality Assessments

Multi-level information fusion to alleviate network congestion

2020 ◽  
Vol 63 ◽  
pp. 248-255 ◽  
Author(s):  
Joel Weijia Lai ◽  
Jie Chang ◽  
L. K. Ang ◽  
Kang Hao Cheong
Keyword(s):  
Information Fusion ◽  
Network Congestion ◽  
Level Information ◽  
Multi Level

Multi-level information fusion for spatiotemporal monitoring in water distribution networks

2015 ◽  
Vol 42 (7) ◽  
pp. 3813-3831 ◽  
Author(s):  
Farzad Aminravan ◽  
Rehan Sadiq ◽  
Mina Hoorfar ◽  
Manuel J. Rodriguez ◽  
Homayoun Najjaran
Keyword(s):  
Information Fusion ◽  
Water Distribution ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Level Information ◽  
Multi Level

Topic identification of text‐based expert stock comments using multi‐level information fusion

2020 ◽  
Author(s):  
Feng Zhao ◽  
Jiahui Zhang ◽  
Zhiyuan Chen ◽  
Xiaofeng Zhang ◽  
Qingsong Xie
Keyword(s):  
Information Fusion ◽  
Topic Identification ◽  
Level Information ◽  
Multi Level

scholarly journals Multi source asynchronous information fusion technology based on cross prompts and its application

2018 ◽  
Vol 246 ◽  
pp. 03021
Author(s):  
Wei Daozhi ◽  
Huang Da ◽  
Huang Shucai
Keyword(s):  
Target Detection ◽  
Information Fusion ◽  
High Tech ◽  
Structure Model ◽  
Fusion Technology ◽  
Fuzzy Decision ◽  
Fusion Model ◽  
Model Based ◽  
Detection And Tracking ◽  
Attack And Defense

Several modern local high-tech wars have shown that the development of war is determined by the precise strike weapons at both ends of attack and defense. In this paper, the urgent requirement of defense ballistic missile target is taken as traction, and the heterogeneous multi-sensor cross-prompt technology is used as support to study the heterogeneous multi-sensor cross-prompt and its application in target detection. On the basis of fully studying the basic theory of heterogeneous multi-sensor cross-prompting, a cross-prompting network structure model based on typical anti-missile combat mission driving and a data fusion model based on asynchronous information are established, and a multi-sensor cross-prompting method based on fuzzy decision is designed. The model and method proposed in this paper are applied to target detection and tracking, and the model and method involved in this paper are verified by simulation.

Distributed Information Fusion Structure Based on Data Fusion Tree

2011 ◽  
Vol 225-226 ◽  
pp. 488-491
Author(s):  
Ying Hua Xue ◽  
Jing Li
Keyword(s):  
Data Fusion ◽  
Information Fusion ◽  
Search Efficiency ◽  
Precise Localization ◽  
Distributed Information ◽  
Traditional Mode ◽  
Level Information ◽  
Multi Level ◽  
Different Levels ◽  
Better Than

A distributed information fusion structure based on data fusion tree is built to realize precise localization and efficient navigation for the mobile robot. The multi-class, multi-level information from robot and environment is fused using different algorithms in different levels, and make the robot have a deeper understanding to the whole environment. Experiments demonstrate that the new model proposed in the paper can improve the positioning precision of robot greatly, and the search efficiency and success rate are also better than traditional mode.

scholarly journals Multi-level information fusion for learning a blood pressure predictive model using sensor data

2020 ◽  
Vol 58 ◽  
pp. 24-39 ◽  
Author(s):  
Monika Simjanoska ◽  
Stefan Kochev ◽  
Jovan Tanevski ◽  
Ana Madevska Bogdanova ◽  
Gregor Papa ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Predictive Model ◽  
Information Fusion ◽  
Sensor Data ◽  
Level Information ◽  
Multi Level
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