Mr. MingShou An | Computer Vision | Research Excellence Award

Posted on by Global Sensor Awards

Mr. MingShou An | Computer Vision | Research Excellence Award

Mr. MingShou An | Computer Vision | Xi’an Technological University | China

Mr. MingShou An is an accomplished researcher and academic professional specializing in Artificial Intelligence–driven sensing systems, with strong expertise in Computer Vision, Deep Learning, and Intelligent Monitoring Technologies. He holds a Ph.D. in an engineering and computing discipline from a recognized Chinese university, where his doctoral research focused on data-driven visual perception, lightweight neural architectures, and intelligent sensing models for real-time environments. Currently affiliated with Xi’an Technological University, Mr. MingShou An has established a solid academic and professional profile through his contributions to national and collaborative research projects addressing smart surveillance, intelligent safety monitoring, and applied AI for sensor-enabled systems. His professional experience spans academic lecturing, research supervision, and applied system development, where he actively bridges theoretical algorithm design with deployable AI solutions for real-world sensing applications, including edge AI and time-sensitive visual analytics. His scholarly output includes 10 Scopus-indexed publications, achieving 15 citations and an h-index of 3, with several works published in IEEE-affiliated conferences and peer-reviewed venues related to intelligent perception and lightweight network design.

Citation Metrics (Scopus)

20

15

10

5

0

Citations
15

Documents
10

h-index
3

🟦 Citations
🟥 Documents
🟩 h-index

View Scopus Profile
 View ORCID Profile

Featured Publication

Ms. Priyanka Manchegowda | Computer Vision | Women Researcher Award

Posted on by Global Sensor Awards

Ms. Priyanka Manchegowda | Computer Vision | Women Researcher Award

Ms. Priyanka Manchegowda | Computer Vision | Amrita Vishwa Vidyapeetham | India

Ms. Priyanka Manchegowda is a results-driven Assistant Professor and researcher, currently pursuing her Ph.D., with over 12 years of combined experience in teaching computer science, academic leadership, and curriculum development. She holds an M.Sc. in Computer Science from Pooja Bhagavat Memorial Mahajana Post Graduate Centre, affiliated with the University of Mysore, Mysuru, India, and has actively contributed to higher education by delivering advanced courses in Exploratory Data Analysis using Python, Digital Image Processing, Design and Analysis of Algorithms, Data Structures, Problem Solving and Programming, Operations Research, Numerical Analysis, Statistical Techniques, Programming in C/C++, and Database Management Systems, consistently achieving strong student satisfaction. Professionally, she has served as an Assistant Professor at SBRR Mahajana First Grade College, Mysuru, from 2013 to 2020, and currently at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus since 2020, where she also contributes as a member of the Board of Studies and has developed curricula in alignment with university standards. In addition to teaching, she has guided Bachelor’s and Master’s students on research projects, focusing her research on computer vision-based human age estimation tailored for Indian medico-legal scenarios, demonstrating expertise in analytical methods, quantitative aptitude, image processing, and programming with Python, C, and C++, alongside database management using MS SQL Server and tools such as MATLAB and Anaconda. Ms. Manchegowda has actively contributed to institutional initiatives and student development, serving as the SWAYAM MOOC Nodal Officer, and as convener for the Rotaract Club and SARANTHA, while also engaging in faculty evaluations for the Internal Quality Assurance Cell (IQAC). She brings strong leadership, teamwork, administrative, and communication skills, alongside a commitment to lifelong learning and academic engagement. Her professional recognition includes citations in Scopus with an h-index reflecting the impact of her scholarly contributions.

Professional Profiles: ORCID | Scopus

Selected Publications

  • Priyanka, M., Divyashree, M., & Madhu, V. (2022). Computer Vision-Based Approach for Estimating Age and Gender using Wrist X-Ray Images.

  • Priyanka, M., Sreekumar, S., & Arsh, S. (2022). Detection of Covid-19 from the Chest X-Ray Images: A Comparison Study between CNN and Resnet-50.

Prof. Zhang Wenli | Computer Vision | Excellence in Research Award

Posted on by Global Sensor Awards

Prof. Zhang Wenli | Computer Vision | Excellence in Research Award 

Prof. Zhang Wenli | Computer Vision | Beijing University of Technology | China

Dr. Wenli Zhang is a distinguished scholar and innovative technology leader currently serving as a Professor in the Faculty of Information Technology at Beijing University of Technology, recognized for impactful contributions in signal and information processing, artificial intelligence, computer vision, 3D point cloud processing, unmanned aerial vehicle inspection technology, and brain-computer interfaces, positioning Dr. Wenli Zhang as a key figure advancing intelligent sensing and human-machine interaction research in China and globally. Building a strong academic foundation through advanced studies in computer science and informatics in both China and Japan, Dr. Wenli Zhang earned a Ph.D. in Engineering from the University of Tokyo, where a passion for applied research and innovation in intelligent systems was further strengthened. Prior to joining academia in China, Dr. Wenli Zhang developed extensive industrial innovation experience as Chief Researcher at Panasonic Corporation’s Tokyo Research Institute, driving real-world AI and vision-based solutions for next-generation automated applications. In her current role, Dr. Wenli Zhang leads interdisciplinary research that spans multiple sectors including smart agriculture, UAV-based intelligent inspection, and medical rehabilitation, effectively bridging fundamental theories with emerging societal needs and technological transformation. With strong collaboration networks and a commitment to promoting scientific excellence, Dr. Wenli Zhang serves actively in influential professional roles, including council member of the Beijing Interdisciplinary Science Society and committee member of the Innovation Engineering Branch of China Creative Studies Institute, contributing leadership within China’s innovation and engineering communities. Skilled in advanced algorithm development, intelligent visual perception, sensor network data fusion, and neural signal decoding, Dr. Wenli Zhang empowers her research team to develop practical systems that enhance automation, sustainability, and accessibility across industries. Her exceptional commitment to teaching and mentorship has earned her the prestigious “Distinguished Teacher” recognition at Beijing University of Technology, reflecting her dual dedication to academic excellence and student success.

Professional Profiles: ORCID  

Selected Publications:

  • Jiang, K., Guo, W., & Zhang, W. (2025). Amodal Segmentation and Trait Extraction of On-Branch Soybean Pods with a Synthetic Dual-Mask Dataset. Sensors.

  • Zhang, W., Peng, X., Bai, T., Wang, H., Takata, D., & Guo, W. (2024). A UAV-Based Single-Lens Stereoscopic Photography Method for Phenotyping the Architecture Traits of Orchard Trees. Remote Sensing.

  • Zhang, W., Peng, X., Cui, G., Wang, H., Takata, D., & Guo, W. (2023). Tree Branch Skeleton Extraction from Drone-Based Photogrammetric Point Cloud. Drones.

  • Li, Y., Liu, B., & Zhang, W. (2024). Driving-Related Cognitive Abilities Prediction Based on Transformer’s Multimodal Fusion Framework. Sensors.

  • Pang, G., Liu, B., & Zhang, W. (2025). Cloud Rehabilitation System Based on Automatic sEMG Signal Processing. Book Chapter.

  • Zhai, R., Gao, Y., Li, G., Ding, Q., Zhang, Y., & Zhang, W. (2025). Control System for Rehabilitation Bionic Hand Based on Precise Control Algorithms.

  • Wang, Y., Pang, G., Liu, B., Li, Y., & Zhang, W. (2025). Gesture Recognition Method Based on Hybrid Classifier Under Non-ideal Conditions.

Prof. Fengyun Cao | Computer Vision Awards | Excellence in Research Award

Posted on by Global Sensor Awards

Prof. Fengyun Cao | Computer Vision Awards | Excellence in Research Award 

Prof. Fengyun Cao, Hefei Normal University, China

Dr. Cao Fengyun is an Associate Professor and Master’s Supervisor at the School of Computer and Artificial Intelligence, Hefei Normal University, where she also serves as Director of the Department of Computer Science and Technology. Her primary research interests include digital image processing, computer vision, and artificial intelligence. Dr. Cao is a member of the Image Application and System Integration Committee of the Chinese Image and Graphics Society and serves on the young editorial board of the international journal INSTRUMENTATION. She is also a reviewer for numerous prestigious journals such as IEEE/CAA Journal of Automatica Sinica, Scientific Reports, and The Journal of Supercomputing. She currently holds the position of Vice President of Science and Technology at the Medical Artificial Intelligence Technology R&D Center, Hefei Innovation Institute. Over the years, she has led various funded research projects, including those focused on depth estimation, remote sensing, and smart control systems. Dr. Cao has authored several high-impact papers and holds 10 authorized invention patents, along with multiple software copyrights and integrated circuit layout designs. Her work has earned her accolades including the “Research Star” award and third prize in the Anhui Province Science and Technology Awards. She has also contributed to the development of local standards in smart systems and information monitoring.

Professional Profile:

SCOPUS

Summary of Suitability:

Dr. Cao Fengyun, an Associate Professor and Director of the Department of Computer Science and Technology at the School of Computer and Artificial Intelligence, Hefei Normal University, is a highly accomplished researcher with a proven track record in digital image processing, computer vision, and artificial intelligence. His outstanding contributions to both theoretical advancements and practical innovations make him an excellent candidate for the Excellence in Research Award.

🎓 Education & Work Experience

  • 👨‍🏫 Teaching Assistant
    School of Computer Science, Hefei Normal University
    📅 June 2013 – November 2017

  • 👨‍🏫 Lecturer
    School of Computer Science, Hefei Normal University
    📅 December 2017 – December 2022

  • 👩‍🏫 Associate Professor
    School of Computer and Artificial Intelligence, Hefei Normal University
    📅 January 2023 – Present

  • 🧠 Vice President of Science and Technology
    Medical AI Technology R&D Center, Hefei Innovation Institute
    📅 November 2024 – Present

🏆 Achievements

  • 📚 Research Areas:
    Digital Image Processing, Computer Vision, Artificial Intelligence

  • 🧪 Research Projects (Host):

    • 🔍 Magnetic Tile Surface Defect Detection (2024–2025)

    • 🤖 Monocular Image Depth Estimation using Deep CNN (2019–2020)

    • 🖼 Single Image Depth Restoration via Low-level Features

    • 🌩 Cloud Tech for Remote Sensing Image Thinning (2018–2019)

    • 🔧 Smart Fire Protection Water Supply System (2025)

    • 📡 High Performance Frequency Hopping Filter Development

    • ⚡ Intelligent Control System for Power Distribution Cabinet (2021)

    • 🔋 Smart-LW Charging Operation and Maintenance System

    • 🧠 Graph Neural Network Intelligent Computing System (Ranked 3rd)

    • 🌐 IoT Equipment Remote Upgrade System (2021)

  • 📄 Representative Papers:

    • ⚙ Electric Bike Testing Dataset – Alexandria Engineering Journal (2024, SCI Zone II TOP)

    • 🎯 YOLOv7-based Anti-target Detection – Traitement du Signal (2023, SCI)

    • 🧩 PCB Defect Recognition via Bi-directional Feature Extraction – Journal of Wuhan University of Technology

    • 🖌 Edge Blur Estimation for Depth Restoration – Journal of Computers

    • 🧠 Image Segmentation and Depth Recovery – Journal of Chinese Image and Graphics

  • 💡 Intellectual Property:

    • 🔬 Invention Patents: 10 (Ranked 1st to 8th) – covering intelligent factories, robotic arms, IoT, and image processing

    • 💻 Software Copyrights: 3 (First author)

    • 🧿 Integrated Circuit Layout Designs: 2 (One authored by him)

🥇 Awards & Honors

  • 🌟 HefeiNormal University Research Star, 2022

  • 🥉 Third Prize – Natural Science Award (Host), Hefei Normal University, 202X

  • 🥉 Third Prize – Anhui Province Science and Technology Award (Ranked 4th), 2021

  • 🏅 Excellence in Science & Technology Progress, Anhui Provincial Computer Society (1st Rank), 2021

Publication Top Notes:

Optimization of the Pure Pursuit algorithm based on real-time error

Prof. Dr. Chao-Ming Wang | Computer Vision | Best Researcher Award

Posted on by Global Sensor Awards

Prof. Dr. Chao-Ming Wang | Computer Vision | Best Researcher Award 

Prof. Dr. Chao-Ming Wang, Department of Digital Media Design / National Yunlin University of Science and Technology, Taiwan

Chao-Ming Wang is a Professor at the Department of Digital Media Design at National Yunlin University of Science and Technology (YunTech), Taiwan, where he has been serving since 2008. He holds a Ph.D. in Computer Science and Information Engineering from National Chiao Tung University, Taiwan, and has a rich career spanning academia and research. Prior to his current role, Dr. Wang was an Associate Professor at Yuan Ze University and has also held senior specialist positions at the National Chung Shan Institute of Science and Technology. His research interests encompass signal processing, computer vision, tech art, and interactive multimedia design. Dr. Wang has been an active leader in professional organizations, including serving as the President of the Taiwan Society of Basic Design and Art from 2010 to 2013. He is also deeply involved in the Taiwanese digital media community through his roles in various associations such as the Taiwan Art & Technology Association and the Taiwan Association of Digital Media Design.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Dr. Chao-Ming Wang is a highly esteemed researcher and academic whose work spans signal processing, computer vision, tech art, and interactive multimedia design. With over four decades of experience in the field, Dr. Wang has made significant contributions to both the academic and industrial domains, establishing himself as a pioneer in integrating technology and art.

🎓 Education

  • Ph.D. in Computer Science and Information Engineering
    🏫 National Chiao Tung University, Hsinchu, Taiwan
    📅 1987–1993

  • M.Sc. in Computer Science and Information Engineering
    🏫 National Chiao Tung University, Hsinchu, Taiwan
    📅 1980–1982

  • B.Sc. in Computer Science
    🏫 National Chiao Tung University, Hsinchu, Taiwan
    📅 1976–1980

💼 Work Experience

  • Professor
    🏫 National Yunlin University of Science and Technology (YunTech), Taiwan
    📅 Aug 2021 – Present
    📍 Department of Digital Media Design

  • Associate Professor
    🏫 YunTech, Taiwan
    📅 2008 – 2021

  • Associate Professor
    🏫 Yuan Ze University, Taoyuan, Taiwan
    📅 2003 – 2008
    📍 Department of Information Communication

  • Senior Specialist
    🏢 National Chung Shan Institute of Science and Technology
    📅 1982 – 2003

🏆 Achievements & Leadership Roles

  • 🧑‍🎓 Head, Dept. of Digital Media Design, YunTech (2010–2013)

  • 🎨 President, Taiwan Society of Basic Design and Art (2010–2013)

  • 💡 Director, Design-led Innovation Center, YunTech (2016–2017)

  • 🧑‍🏫 Executive Director, Taiwan Association of Digital Media Design (2015–2021)

  • 🤝 Director, Taiwan Art & Technology Association (2013–2023)

  • 🏅 Director of Honor, Taiwan Society of Basic Design and Art (2014–present)

  • 🧠 Permanent Member, Chinese Image Processing and Pattern Recognition Society (2003–present)

🔬 Research Interests

  • 🎛️ Signal Processing

  • 👁️ Computer Vision

  • 🖼️ Tech Art

  • 🎮 Interactive Multimedia Design

Publication Top Notes:

Design of an Interactive Exercise and Leisure System for the Elderly Integrating Artificial Intelligence and Motion-Sensing Technology

Combining Interactive Technology and Visual Cognition—A Case Study on Preventing Dementia in Older Adults

The design of a new interactive multimedia system based on computer vision and multi-sensing techniques for the traditional ritual process

Design of a Gaze-Controlled Interactive Art System for the Elderly to Enjoy Life

Design of a Technology-Based Magic Show System with Virtual User Interfacing to Enhance the Entertainment Effects

Design and Assessment of an Interactive Role-Play System for Learning and Sustaining Traditional Glove Puppetry by Digital Technology

The Design of a Novel Digital Puzzle Gaming System for Young Children’s Learning by Interactive Multi-Sensing and Tangible User Interfacing Techniques

Using Digital Technology to Design a Simple Interactive System for Nostalgic Gaming to Promote the Health of Slightly Disabled Elderly People

Combining Augmented Reality and Multi-User Remote Collaboration to Improve Sustainable Agriculture and Economy

Ms. Congying Sun | Object Detection Awards | Best Researcher Award

Posted on by Global Sensor Awards

Ms. Congying Sun | Object Detection Awards | Best Researcher Award 

Ms. Congying Sun, Xi’an University of Technology, China

Congying Sun, a native of Xianyang City, Shaanxi Province, is an emerging researcher specializing in control science, engineering, and multi-modal remote sensing technologies. She earned her Bachelor’s degree in Printing Engineering from Xi’an University of Technology in 2022 and is currently pursuing a Master’s degree in Control Science and Engineering at the same institution, expected to graduate in 2025. Her professional experience includes a tenure at the Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, where she played a pivotal role in developing an infrared-visible aircraft image dataset and deploying state-of-the-art infrared small target detection models. Congying has demonstrated her ability to merge academic excellence with practical application through her contributions to national and engineering projects, including research on multi-source collaborative intelligent perception technology for aircraft and non-cooperative multi-target classification and cognition technology.

Professional Profile:

ORCID

Suitability of Congying Sun for the Best Researcher Award

Congying Sun demonstrates exceptional qualifications and accomplishments, making her an outstanding candidate for the Research for Best Researcher Award. Below is a summary of her key achievements and strengths

🎓 Education

  • Master’s Degree in Control Science and Engineering (August 2022 – July 2025)
    🏫 Xi’an University of Technology
  • Bachelor’s Degree in Printing Engineering (September 2018 – July 2022)
    🏫 Xi’an University of Technology

🧑‍💻 Professional Experience

Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences (July 2023 – August 2024)

  • 📸 Independently created an infrared-visible aircraft image dataset, including camera selection, data collection, and image annotation.
  • 📝 Authored project proposals, research papers, and patents with great precision.
  • 🤖 Developed and deployed infrared small target detection models and multi-modal remote sensing image fusion detection models.

🚀 Research Projects

  • Multi-source Collaborative Intelligent Perception Technology for Aircraft (August 2023 – June 2024) ✈️
  • Non-cooperative Multi-target Classification and Cognition Technology (October 2023 – March 2024) 🎯

🏅 Achievements

  • Granted Invention Patents:
    • 📜 Infrared Small Target Detection Method (CN118762159A)
    • 📜 Multi-modal Feature Fusion Target Detection Model and Method (CN118865046A)

💡 Research Interests

🔍 Machine Learning | 🌍 Multi-modal Remote Sensing | 🎯 Target Detection

Congying Sun’s innovative approach, technical expertise, and impactful contributions to cutting-edge research make her a rising star in the field of control science and engineering. 🌟

Publication Top Notes:

Location-Guided Dense Nested Attention Network for Infrared Small Target Detection

MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images