Wenxuan Li

ORCID: 0009-0008-7675-8711
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About
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Research Areas
  • Advanced machining processes and optimization
  • Manufacturing Process and Optimization
  • Advanced Neural Network Applications
  • Advanced Image and Video Retrieval Techniques
  • Domain Adaptation and Few-Shot Learning
  • Industrial Vision Systems and Defect Detection

Minzu University of China
2024

National University of Singapore
2000

Few-shot segmentation (FSS) is a challenging task because the same class of targets in support and query image may have different scale, texture background information. Prototype learning (PL) current mainstream FSS method, which characterizes interaction between prototype vector feature. However, commonly based on global average pooling only contains first-order feature information, vulnerable to varying appearance similar target diversity background. Moreover, auxiliary information not...

10.1109/access.2024.3350747 article EN cc-by-nc-nd IEEE Access 2024-01-01

A hybrid feature recognition system using hints, graph manipulations and artificial neural networks for the of overlapping machining features is presented. Based on enhanced attributed adjacency (EAAG) representation virtual link (VLG) a designed part, face loops (F-loops) are defined as generalized hints. They then extracted from EAAG vector calculations, relationships between F-loops established. Next, manipulated according to six types relationship build F-loop subgraphs (FLGs), which...

10.1243/0954405001518107 article EN Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture 2000-08-01
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