Xin Su | Temporal Data Patterns | Best Researcher Award

Assoc Prof Dr. Xin Su | Temporal Data Patterns | Best Researcher Award

Wuhan University | China

Publication Profile

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EARLY ACADEMIC PURSUITS ๐Ÿ“š

Dr. Xin Suโ€™s academic journey began with his pursuit of a Ph.D. at Tรฉlรฉcom ParisTech, where his foundational work in remote sensing and computer vision laid the groundwork for his later breakthroughs. His early research on multi-temporal image processing set the stage for his significant contributions in the field.

PROFESSIONAL ENDEAVORS ๐Ÿ’ผ

Following his postdoctoral research at INRIA, Dr. Su took on the role of Associate Professor at Wuhan University. Over the years, his research has expanded into disaster management and urban development, where he has actively led projects with direct applications for societal benefit.

CONTRIBUTIONS AND RESEARCH FOCUSย  ON Temporal Data Patterns๐ŸŒ

Dr. Suโ€™s most significant contributions are in multi-temporal remote sensing change detection and classification mapping. His research has had tangible effects in managing natural disasters, such as mapping the 2022 Henan flood and the 2023 Turkey earthquake. His focus on extracting actionable information from remote sensing data has provided critical insights for emergency responses and urban development.

IMPACT AND INFLUENCE ๐ŸŒ

Dr. Su’s research has influenced not only academic thought but also practical applications in various industries. His involvement in projects funded by the National Natural Science Foundation of China has provided the government with tools for urban monitoring, disaster management, and land-use planning.

ACADEMIC CITATIONS ๐Ÿ“ˆ

With over 1,000 citations to his work, Dr. Su has garnered recognition for his research, with more than 40 SCI papers published in top-tier journals. His research contributions have significantly advanced the fields of remote sensing and computer vision, ensuring their practical use in tackling global challenges.

LEGACY AND FUTURE CONTRIBUTIONS ๐Ÿ”ฎ

Dr. Xin Su is poised to leave a lasting legacy in the fields of remote sensing and artificial intelligence. His ongoing research, particularly in urban development and disaster management, will continue to shape the future of environmental monitoring and response strategies.

KEY RESEARCH FOCUS ๐Ÿ”

  • Remote sensing image processing
  • Multi-temporal remote sensing information extraction
  • Computer vision applications in disaster response and urban planning

COLLABORATIONS AND PARTNERSHIPS ๐Ÿค

Dr. Su collaborates with esteemed researchers like Prof. Florence TUPIN (Telecom ParisTech), Prof. Christine GUILLEMOT (INRIA), and others at Wuhan University, including Prof. Liangpei Zhang and Prof. Qiangqiang Yuan, to push the boundaries of remote sensing research.

PROFESSIONAL MEMBERSHIPS ๐Ÿ…

  • IEEE Member
  • CSIG (China Society of Image and Graphics) Member

AWARD CATEGORY PREFERENCE ๐Ÿ†

Dr. Su has applied for the Best Researcher Award, underscoring his groundbreaking contributions to remote sensing and AI-driven applications in environmental monitoring and urban planning.

TOP NOTES PUBLICATIONS ๐Ÿ“š

Satellite video super-resolution via multiscale deformable convolution alignment and temporal grouping projection
    • Authors: Y Xiao, X Su, Q Yuan, D Liu, H Shen, L Zhang
    • Journal: IEEE Transactions on Geoscience and Remote Sensing
    • Year: 2021
Cloud removal with fusion of high resolution optical and SAR images using generative adversarial networks
    • Authors: J Gao, Q Yuan, J Li, H Zhang, X Su
    • Journal: Remote Sensing
    • Year: 2020
A coarse-to-fine boundary refinement network for building footprint extraction from remote sensing imagery
    • Authors: H Guo, B Du, L Zhang, X Su
    • Journal: ISPRS Journal of Photogrammetry and Remote Sensing
    • Year: 2022
Space-time super-resolution for satellite video: A joint framework based on multi-scale spatial-temporal transformer
    • Authors: Y Xiao, Q Yuan, J He, Q Zhang, J Sun, X Su, J Wu, L Zhang
    • Journal: International Journal of Applied Earth Observation and Geoinformation
    • Year: 2022
Two-Step Multitemporal Nonlocal Means for Synthetic Aperture Radar Images
    • Authors: X Su, CA Deledalle, F Tupin, H Sun
    • Journal: Geoscience and Remote Sensing, IEEE Transactions on
    • Year: 2014
DymSLAM: 4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation
    • Authors: C Wang, B Luo, Y Zhang, Q Zhao, L Yin, W Wang, X Su, Y Wang, C Li
    • Journal: IEEE Robotics and Automation Letters
    • Year: 2020