Baijian Yin

ORCID: 0000-0002-8757-6082
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About
Contact & Profiles
Research Areas
  • Fault Detection and Control Systems
  • Advanced Graph Neural Networks
  • Semantic Web and Ontologies
  • Neural Networks and Applications
  • Vehicular Ad Hoc Networks (VANETs)
  • Traffic Prediction and Management Techniques
  • Topic Modeling
  • Evacuation and Crowd Dynamics
  • Distributed and Parallel Computing Systems
  • Structural Integrity and Reliability Analysis
  • Fuzzy Logic and Control Systems
  • Spectroscopy and Chemometric Analyses

Amazon (United States)
2023-2024

The Aerospace Corporation
1988

A complex logic query in a knowledge graph refers to expressed form that conveys meaning, such as where did the Canadian Turing award winner graduate from? Knowledge reasoning-based applications, dialogue systems and interactive search engines, rely on ability answer queries fundamental task. In most graphs, edges are typically used either describe relationships between entities or their associated attribute values. An value can be categorical numerical format, dates, years, sizes, etc....

10.1145/3580305.3599399 article EN Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2023-08-04

This paper describes a suite of target cueing algorithms which has been developed for the recognition ship targets in open ocean through FLIR Imagery. Imaging prepro cessing is first used to remove pattern and temporal noise. A relaxation technique implemented extract target's silhouette. The superstructure profile then obtained classification performed based on low-order coefficients discrete Fourier transform profile. approach was found have 93% accuracy short ranges (7-11 miles) 70% long...

10.1117/12.944286 article EN Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE 1988-05-03

This paper describes the design of a binary tree classifier for ship targets. The methodology is general enough so that it can be utilized other classification problems. A hierarchical clustering procedure employed to i) discover underlying structure data, and ii) construct skeleton. best feature subset, at each nonterminal node skeleton, selected through multivariate stepwise which attempts maximize class separability. Further, this approach continues, until probability error with respect...

10.1117/12.936656 article EN Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE 1984-01-09
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