Peixian Zhuang | Underwater Autonomous Vehicles | Best Researcher Award

Best Researcher Award

Peixian Zhuang
University of Science and Technology Beijing, China

Peixian Zhuang
Affiliation University of Science and Technology Beijing
Country China
Scopus ID 56435653500
Documents 84
Citations 5,872
h-index 26
Subject Area Underwater Autonomous Vehicles
Event International Robotics and Automation Awards
ORCID 0000-0002-7143-9569

Peixian Zhuang is identified with the University of Science and Technology Beijing, China. The supplied researcher profile reports 84 documents, 5,872 citations, and an h-index of 26. The research topics provided for this article concern underwater image enhancement, image dehazing, and computational image restoration. These details offer an initial overview of the research profile and should be verified against the relevant academic records before publication [1].

Abstract

This article presents a research profile of Peixian Zhuang, affiliated with the University of Science and Technology Beijing, China. The supplied publication topics address underwater image enhancement, remote-sensing image dehazing, and Bayesian Retinex methods. These research areas relate to improving image visibility, contrast, and quality under challenging imaging conditions. The profile also summarizes reported bibliometric indicators and outlines considerations for evaluating research achievements for the Best Researcher Award. Publication attribution and citation metrics require verification against authoritative academic sources [1].

Keywords

Peixian Zhuang; Best Researcher Award; underwater image enhancement; underwater autonomous vehicles; image dehazing; contrast enhancement; color restoration; Bayesian Retinex; remote sensing; computer vision; robotics and automation; research impact.

Introduction

Underwater imaging supports marine exploration, autonomous navigation, and robotic inspection. However, light absorption, scattering, and reduced contrast can limit image quality. Image enhancement and dehazing techniques aim to improve visual information for subsequent analysis. The supplied publication titles provide a basis for examining these research themes and their potential relevance to underwater vision systems [2].

Research Profile

Peixian Zhuang is associated with the University of Science and Technology Beijing in the supplied information. The profile lists Scopus Author ID 56435653500, 84 documents, 5,872 citations, and an h-index of 26. These indicators offer a preliminary overview of scholarly activity. The current affiliation, publication records, and bibliometric figures should be confirmed using the official author profile [3].

Research Contributions

The supplied research titles cover underwater image enhancement, remote-sensing image dehazing, and Bayesian Retinex techniques. These topics address visual degradation, color preservation, and contrast improvement in challenging environments. Such methods may support computer vision and autonomous systems. Specific methodological advances and individual contributions must be established by reviewing the original publications and their reported experimental results [2].

Publications

The following titles were supplied for inclusion in the researcher profile. Their full bibliographic details, including authors, publication years, journals or conference proceedings, page ranges, and DOIs, must be verified against the original records. The entries below are preliminary title-based references rather than complete APA citations [3].

Research Impact

The supplied bibliometric figures indicate reported scholarly publication and citation activity. Research on image enhancement and dehazing can contribute to clearer visual data for marine observation, remote sensing, and computer vision. A comprehensive assessment of research impact should consider verified citations, methodological reliability, reproducibility, and demonstrated applications rather than relying exclusively on numerical indicators [1].

Award Suitability

The supplied publication and citation indicators provide preliminary context for considering Peixian Zhuang for the Best Researcher Award at the International Robotics and Automation Awards. Evaluation should examine verified authorship, research originality, publication quality, reproducibility, and practical relevance. Final eligibility and recognition should follow the award organizers’ published criteria and an independent assessment of the supporting evidence [2].

Conclusion

The supplied profile connects Peixian Zhuang with research topics in underwater image enhancement and computational image restoration. The reported bibliometric indicators provide an initial overview of scholarly activity, while the listed publication titles suggest relevant technical themes. Verification of author attribution, publication metadata, and current citation information is necessary before final publication or formal award consideration [3].

References

    1. Underwater Image Enhancement via Minimal Color Loss and Locally Adaptive Contrast Enhancement.
      https://www.researchgate.net/publication/361075234
    2. BDSA: Remote Sensing Image Dehazing via Fusing Brightness Decomposition and Saturation Adjustment.
      https://www.researchgate.net/publication/400439952
    3. Bayesian retinex underwater image enhancement.
      https://www.sciencedirect.com/science/article/abs/pii/S095219762100018X.