Education:
Mr. Yikun Pan has a robust educational background in computer engineering and information technology. He earned his Bachelor’s degree in Science and Computer Engineering from the Open University of Hong Kong, completing his studies from September 2016 to June 2018. He then pursued a Master’s degree in Electronic and Information Engineering at the Hong Kong Polytechnic University, which he completed from September 2018 to June 2020. Currently, he is advancing his academic career as a part-time PhD student at the Hong Kong Polytechnic University, a program he began in September 2021 and will conclude in 2024. This comprehensive educational foundation equips him with the knowledge and skills necessary for impactful research in his chosen fields.
Professional Experience:
Mr. Yikun Pan has a diverse professional experience rooted in his strong academic background in computer engineering and electronic information engineering. He began his research journey while studying for his Bachelor’s degree at the Open University of Hong Kong, where he completed his final year project from September 2017 to June 2018, culminating in a thesis titled “Design and Development of a Haptic Orthosis for Lower Limb Training.” This project marked his entry into applied engineering, emphasizing the intersection of technology and rehabilitation. During his Master’s studies at the Hong Kong Polytechnic University from February 2019 to June 2020, Mr. Pan focused on deep learning techniques, completing his dissertation on “Image Segmentation and Inpainting Based on Deep Learning.” This work provided him with valuable skills in advanced image processing methodologies. In September 2020, he contributed as the second author to the publication “Stereoscopic Image Reflection Removal Based on Wasserstein Generative Adversarial Network,” further establishing his proficiency in generative adversarial networks. Mr. Pan continued to collaborate on innovative projects, co-authoring a paper in June 2021 titled “Design, Development, and Evaluation of Upper and Lower Limb Orthoses with Intelligent Control for Rehabilitation.” His dedication to improving rehabilitation technology was evident in this research. Most recently, he has published two significant papers: “Blur Detection for Surveillance Camera System” in September 2022 and “Solving the Imbalanced Dataset Problem in Surveillance Image Blur Classifications” in September 2024, both as the first author. These publications reflect his commitment to advancing knowledge in computer vision and machine learning applications.
Research Interests:
Mr. Yikun Pan’s research interests lie at the intersection of multimedia technology, deep learning, and computer vision. His work focuses on developing innovative solutions that enhance the effectiveness and efficiency of visual data processing and interpretation. He is particularly passionate about applying deep learning techniques to improve image segmentation and inpainting, as demonstrated in his Master’s dissertation. Mr. Pan is also interested in exploring generative adversarial networks (GANs) for applications such as image reflection removal, showcasing his commitment to advancing state-of-the-art methodologies in the field. Additionally, his ongoing research includes addressing challenges related to surveillance systems, particularly in the context of blur detection and imbalanced datasets. By leveraging deep learning approaches, he aims to enhance the reliability of surveillance camera systems and improve the accuracy of image classifications in real-world scenarios. Through his Ph.D. studies, Mr. Pan aspires to contribute significantly to the fields of multimedia and computer vision, aiming for practical applications that can benefit society and address pressing technological challenges.
Skills:
Mr. Yikun Pan possesses a strong skill set that supports his research in multimedia, deep learning, and computer vision. He is proficient in programming languages such as Python and MATLAB, and has extensive experience with deep learning frameworks like TensorFlow and PyTorch. His expertise includes advanced image analysis techniques, including image segmentation, inpainting, and blur detection, as well as generative adversarial networks (GANs). Mr. Pan excels in conducting literature reviews and articulating research findings through academic writing, as demonstrated by his publications. His collaborative mindset and problem-solving abilities further enhance his contributions to research projects.
Conclusion:
In summary, Mr. Yikun Pan is an outstanding candidate for the Research for Best Researcher Award. His solid educational background, extensive research experiences, and significant contributions to the fields of multimedia, deep learning, and computer vision highlight his potential as a leading researcher. His dedication to advancing knowledge and developing innovative solutions positions him as an exemplary candidate for this prestigious award. Mr. Pan’s work not only reflects his expertise but also his passion for leveraging technology to address complex challenges in society.
Publication Top Noted:
Solving the imbalanced dataset problem in surveillance image blur classification
- Journal: Engineering Applications of Artificial Intelligence
- Year: 2024
- Volume: 138
- Article Number: 109345
- Contributors: Pan, Y.; Tseng, S.-H.; Chan, T.T.-L.; Chan, Y.-L.; Lun, D.P.-K.
Blur Detection for Surveillance Camera System
- Conference: 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC 2022)
- Year: 2022
- Pages: 1879–1884
- Contributors: Pan, Y.; Tsang, S.-H.; Chan, Y.-L.; Lun, D.P.K.
Stereoscopic image reflection removal based on Wasserstein Generative Adversarial Network
- Conference: 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP 2020)
- Year: 2020
- Pages: 148–151
- Paper ID: 9301892
- Contributors: Wang, X.; Pan, Y.; Lun, D.P.K.