Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

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Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Excellence in Research Award

Assist. Prof. Dr. Hye-Youn Lim | Computer Vision | Dong-A University | South Korea

Assist. Prof. Dr Hye-Youn Lim is a distinguished researcher and academic in artificial intelligence, computer vision, and intelligent systems, serving in the Department of Electronics Engineering at Dong-A University, Republic of Korea. Hye-Youn Lim obtained her Ph.D. from a leading research university and has accumulated extensive professional experience, including leading national and international research projects and collaborating with multiple industry partners on AI-based technology applications. Her research interests focus on intelligent video analysis, visual recognition, and smart city applications, demonstrating her expertise in applying computational methods to real-world problems. Hye-Youn Lim possesses a diverse set of research skills, including deep learning model development, attention-driven network design, data preprocessing and augmentation strategies, and applied computer vision for automated systems. Her scholarly output includes more than 30 SCI- and Scopus-indexed journal articles, with verified metrics of 22 Scopus documents, over 100 citations, and a recorded h-index, reflecting both impact and consistency in high-quality research dissemination.

Citation Metrics (Scopus)

120

90

60

30

0

Citations
105

Documents
22

h-index
3

Citations
Documents
h-index

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 View ORCID Profile

Featured Publications

Mr. Suresha R | Computer Vision Awards | Excellence in Research Award

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Mr. Suresha R | Computer Vision Awards | Excellence in Research Awardย 

Mr. Suresha R | Computer Vision Awards | Amrita Vishwa Vidyapeetham | India

Mr. Suresha R. is a results-driven educator and technologist with over six years of combined experience in teaching computer science and academic leadership. He holds an M.Sc. in Computer Science and has qualified in UGC-NET and K-SET, while currently pursuing a Ph.D. Mr. Suresha R. has demonstrated expertise in curriculum design and research, particularly focusing on AI in autonomous solutions and computer vision applications. In his professional career, Mr. Suresha R. has served as an Assistant Professor at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus, and at SBRR Mahajana First Grade College, Mysuru, where he delivered advanced courses in Computer Vision, Digital Image Processing, Pattern Recognition, Computational Intelligence, Computer Graphics, Machine Learning, Exploratory Data Analysis, R Programming, Information Retrieval, Data Mining, Numerical Analysis, and Operations Research, consistently achieving high student satisfaction. His research interests encompass small traffic sign detection and recognition in challenging scenarios using computer vision and LiDAR-based techniques with ROS2 framework, deep learning-based vehicle detection and distance estimation for autonomous systems, motion blur image restoration, wild animal recognition through vocal analysis, and SVM-based medical image classification. Mr. Suresha . possesses strong research skills in Python, MATLAB, ROS2, machine learning, deep learning, image processing, and data analysis. He has successfully guided Bachelor’s and Master’s students in research projects, fostering innovation and academic growth. His academic contributions are recognized through multiple publications in prestigious journals and conferences, including IEEE Access, Procedia Computer Science, ICCCNT, CCEM, ICECAA, and INDIACom. Mr. Suresha . has a proven record of collaborating in interdisciplinary teams, effectively communicating complex technical concepts, and mentoring students to achieve excellence in research and practical applications. His dedication to lifelong learning and active engagement in both teaching and research demonstrates his commitment to advancing knowledge in computer science and autonomous systems. Throughout his career, Suresha ย has received awards and recognitions for research excellence, contributing to the development of sustainable and intelligent solutions in the field of computer vision and AI. Overall, Mr. Suresha exemplifies a passionate and innovative professional, bridging theoretical foundations with applied research, and continues to make significant contributions to academia and technology

Professional Profiles:ย ORCID

Selected Publicationsย 

  1. Suresha, R., Manohar, N., Ajay Kumar, G., & Singh, R. (2024). Recent advancement in small traffic sign detection: Approaches and dataset.

  2. Suresha, R., Manohar, N., & Jipeng, T. (2024). Two-stage traffic sign classification system.

  3. Sudharshan Duth, P., Manohar, N., Suresha, R., Priyanka, M., & Jipeng, T. (2024). Wild animal recognition: A vocal analysis.

  4. Suresha, R., Jayanth, R., & Shriharikoushik, M. A. (2023). Computer vision approach for motion blur image restoration system.

  5. Srinivasa, C., Suresha, R., Manohar, N., Dharun, G. K., Sheela, T., & Jipeng, T. (2023). Deep learning-based techniques for precise vehicle detection and distance estimation in autonomous systems.

  6. Suresha, R., Devika, K. M., & Prabhu, A. (2022). Support vector machine classifier based lung cancer recognition: A fusion approach.

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Best Researcher Award

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Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Best Researcher Award

Mr. Ahmet Serhat Yildiz | Computer Vision Awards | Brunel University of London | United Kingdom

Mr. Ahmet Serhat Yildiz is an emerging researcher in sensing technology with growing expertise in machine learning, deep learning, embedded systems, and multi-sensor fusion, demonstrating strong potential for advanced research roles and academic leadership. He is currently pursuing his PhD in Electronic and Computer Engineering at Brunel University London, where he focuses on real-time object detection, semantic 3D depth sensing, LiDARโ€“camera fusion, and intelligent autonomous perception systems, aligning closely with sensing applications in robotics, transportation, surveillance, and industrial automation. His academic foundation includes degrees in electronics, electrical engineering, business management, and extensive English language training, providing a multidisciplinary perspective that strengthens his analytical and communication abilities. His professional experience includes roles as a Graduate Teaching Assistant in digital design, embedded systems, and computer architecture, as well as serving as an IoT facilitator, where he mentored learners and contributed to community-oriented technology initiatives. Mr. AHMET SERHAT YILDIZ has developed notable research projects, including FPGA-based embedded game systems, PLC-controlled industrial automation setups, and biomedical sensing circuits for pulse wave velocity measurement, demonstrating strong hands-on engineering skills. His research portfolio includes Scopus-indexed publications on YOLO-based detection models, sensor fusion for autonomous vehicles, and real-time navigation using LiDAR and deep learning frameworks, reflecting his ability to integrate theory with practical sensing applications. His technical skills include Python, PyTorch, embedded C, FPGA development, digital circuit design, PLC programming, and multi-sensor signal processing, enabling him to contribute to both algorithmic and hardware-oriented research environments. His achievements include scholarly publications, increasing citation impact, and recognition through participation in international conferences and multidisciplinary research projects.

Professional Profiles: ORCID | Google Scholar

Featured Publicationsย 

  1. Alkandary, K., Yildiz, A. S., & Meng, H. (2025). A comparative study of YOLO series (v3โ€“v10) with DeepSORT and StrongSORT: A real-time tracking performance study. Electronics.

  2. Tunali, M. M., Yildiz, A., & ร‡akar, T. (2022). Steel surface defect classification via deep learning. International Conference on Computer Science and Engineering (UBMK).

  3. Yildiz, A. S., Meng, H., & Swash, M. R. (2025). Real-time object detection and distance measurement enhanced with semantic 3D depth sensing using cameraโ€“LiDAR fusion. Applied Sciences.

  4. Tunali, M. M., Sayar, A., Aslan, Y., Mutlu, ฤฐ., & ร‡akar, T., including Yildiz, A. (2023). Enhancing quality control in plastic injection production: Deep learning-based detection and classification of defects. International Conference on Computer Science and Engineering (UBMK).

  5. Yฤฑldฤฑz, A., MiลŸe, P., ร‡akar, T., TerzibaลŸฤฑoฤŸlu, A. M., & ร–ke, D. (2023). Spine posture detection for office workers with hybrid machine learning. International Conference on Computer Science and Engineering (UBMK).

  6. Yildiz, A. S., Meng, H., & Swash, M. R. (2025). YOLOv8โ€“LiDAR fusion: Increasing range resolution based on image-guided sparse depth fusion in self-driving vehicles. Lecture Notes in Networks and Systems.

  7. Yildiz, A. S., Meng, H., & Swash, M. R. (2024). A multi-sensor fusion approach to real-time birdโ€™s-eye view navigation: YOLOv8 and LiDAR integration for autonomous systems. Korkut Ata Scientific Research Conference Proceedings.

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

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

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.

๐ŸŽ“ Education

  • Ph.D. in Computer Science and Information Engineering
    ๐Ÿซ National Chiao Tung University, Hsinchu, Taiwan
    ๐Ÿ“… 1987โ€“1993

  • M.Sc. in Computer Science and Information Engineering
    ๐Ÿซ National Chiao Tung University, Hsinchu, Taiwan
    ๐Ÿ“… 1980โ€“1982

  • B.Sc. in Computer Science
    ๐Ÿซ National Chiao Tung University, Hsinchu, Taiwan
    ๐Ÿ“… 1976โ€“1980

๐Ÿ’ผ Work Experience

  • Professor
    ๐Ÿซ National Yunlin University of Science and Technology (YunTech), Taiwan
    ๐Ÿ“… Aug 2021 โ€“ Present
    ๐Ÿ“ Department of Digital Media Design

  • Associate Professor
    ๐Ÿซ YunTech, Taiwan
    ๐Ÿ“… 2008 โ€“ 2021

  • Associate Professor
    ๐Ÿซ Yuan Ze University, Taoyuan, Taiwan
    ๐Ÿ“… 2003 โ€“ 2008
    ๐Ÿ“ Department of Information Communication

  • Senior Specialist
    ๐Ÿข National Chung Shan Institute of Science and Technology
    ๐Ÿ“… 1982 โ€“ 2003

๐Ÿ† Achievements & Leadership Roles

  • ๐Ÿง‘โ€๐ŸŽ“ Head, Dept. of Digital Media Design, YunTech (2010โ€“2013)

  • ๐ŸŽจ President, Taiwan Society of Basic Design and Art (2010โ€“2013)

  • ๐Ÿ’ก Director, Design-led Innovation Center, YunTech (2016โ€“2017)

  • ๐Ÿง‘โ€๐Ÿซ Executive Director, Taiwan Association of Digital Media Design (2015โ€“2021)

  • ๐Ÿค Director, Taiwan Art & Technology Association (2013โ€“2023)

  • ๐Ÿ… Director of Honor, Taiwan Society of Basic Design and Art (2014โ€“present)

  • ๐Ÿง  Permanent Member, Chinese Image Processing and Pattern Recognition Society (2003โ€“present)

๐Ÿ”ฌ Research Interests

  • ๐ŸŽ›๏ธ Signal Processing

  • ๐Ÿ‘๏ธ Computer Vision

  • ๐Ÿ–ผ๏ธ Tech Art

  • ๐ŸŽฎ Interactive Multimedia Design

Publicationย 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 Cognitionโ€”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 Childrenโ€™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