Miao Wang

Affiliations:
  • Shanghai Jiao Tong University, School of Aeronautics and Astronautics, China
  • Science and Technology on Avionics Integration Laboratory, China National Aeronautical Radio Electronics Research Institute, Shanghai, China


According to our database1, Miao Wang authored at least 14 papers between 2013 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2022
Multi-scale attention-based pseudo-3D convolution neural network for Alzheimer's disease diagnosis using structural MRI.
Pattern Recognit., 2022

2019
Multiple-Object-Tracking Algorithm Based on Dense Trajectory Voting in Aerial Videos.
Remote. Sens., 2019

A Novel Probability Evaluation Method Based on Fuzzy Fault Dependent Matrix.
Proceedings of the Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery - Proceedings of the 15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2019), Kunming, China, July 20-22, 2019, 2019

Availability Analysis of Electronic Flight Instrument System Based on Dynamic Fault Dependent Matrix.
Proceedings of the 19th IEEE International Conference on Communication Technology, 2019

Availability assessment of avionics display system based on fuzzy fault dependent matrix.
Proceedings of the 2nd International Conference on Artificial Intelligence and Pattern Recognition, 2019

2018
Rapid Ground Car Detection on Aerial Infrared Images.
Proceedings of the 2018 International Conference on Image and Graphics Processing, 2018

2017
Multi-platform fire control strike track planning method based on deep enhance learning.
Proceedings of the 16th IEEE/ACIS International Conference on Computer and Information Science, 2017

Research on big data management and analysis method of multi-platform avionics system.
Proceedings of the 16th IEEE/ACIS International Conference on Computer and Information Science, 2017

2014
Mining Closed Strong Association Rules by Rule-growth in Resource Effectiveness Matrix.
J. Softw., 2014

Efficient Mining Maximal Variant Usage and Low Usage Biclusters in Discrete Function-Resource Matrix.
J. Comput., 2014

Mining Frequent Closed Patterns using Sample-growth in Resource Effectiveness Data.
J. Comput., 2014

2013
DoCluster: Efficient mining maximal biclusters without candidate maintenance in the function-resource matrix.
Proceedings of the 6th International Conference on Biomedical Engineering and Informatics, 2013

CSRule: Efficient mining of closed strong association rules in the resource effectiveness matrix.
Proceedings of the 6th International Conference on Biomedical Engineering and Informatics, 2013

Efficient Mining Maximal Variant and Low Usage Rate Biclusters without Candidate Maintenance in Real Function-Resource Matrix: The DeCluster Algorithm.
Proceedings of the Advanced Data Mining and Applications - 9th International Conference, 2013


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