Wen Cheng Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
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Biography and Research Information
OverviewAI-generated summary
Wen Cheng's research focuses on computational methods for analyzing biological data, particularly in the areas of protein interactions and computer vision. Cheng has investigated graph-based approaches for predicting protein-RNA interactions, utilizing reduced amino acid alphabets. In the field of computer vision, Cheng's work includes developing object localization techniques using Vision Transformers, incorporating loss functions based on Intersection over Union (IOU) and Mean Squared Error. Additionally, Cheng has explored comparative analyses of color invariants for image retrieval. With an h-index of 3 and 14 total publications, Cheng has recently been active in research, with publications in 2023 and 2025. Cheng collaborates with Hong Cheng at Southern Arkansas University, with whom they share one publication.
Metrics
- h-index: 3
- Publications: 14
- Citations: 16
Selected Publications
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Comparative Analysis of Color Invariants for Image Retrieval (2025)
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Object Localization Using Vision Transformer with a Loss Function Based on IOU and Mean Squared Error (2023)
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A Graph Method for Predicting Protein-RNA Interaction Using Reduced Amino Acid Alphabets (2023)
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