Ms. Minkyung Sung | Image Segmentation Awards | Best Researcher Award

Posted on 20/01/2025 by ScienceFather

Ms. Minkyung Sung | Image Segmentation Awards | Best Researcher Award

Ms. Minkyung Sung, Chung-Ang University, South Korea

Min-Kyung Sung is a dedicated Master’s student at the Department of Artificial Intelligence at Chung-Ang University, where she studies under the guidance of Professor Jaesung Lee. With a Bachelor of Science degree in Software from Anyang University, she has developed a strong foundation in artificial intelligence and image segmentation, particularly focusing on on-device AI applications. Min-Kyung has made significant contributions to the field, publishing her work in prominent international conferences such as the IEEE International Conference on Consumer Electronics and presenting research on open vocabulary segmentation based on vision-language pre-trained models. Her recent projects include developing a deep learning CT shortening algorithm for structural adhesive inspection at Hyundai and an AI pediatric behavioral analysis system for children with autism spectrum disorder (ASD). Recognized for her excellence, she received the Best Paper Award at the Spring Academic Conference of the Korean Society for Emotion and Sensibility in 2023. Proficient in Python, LaTeX, and various machine learning tools such as PyTorch and TensorFlow, Min-Kyung is poised to make significant advancements in the artificial intelligence domain.

Professional Profile:

GOOGLE SCHOLAR

Suitability for the Research for Best Researcher Award: Min-Kyung Sung

Min-Kyung Sung is an exemplary candidate for the Research for Best Researcher Award, showcasing significant achievements in artificial intelligence and image segmentation through a blend of rigorous academic training and impactful research contributions.

🎓 Education

Master’s Student in Department of AI, Chung-Ang University (2023 – Present)
Academic Adviser: Prof. Jaesung Lee
B.S. in Software Engineering at Anyang University (2019 – 2023)

💼 Work Experience

Researcher at Chung-Ang University, focusing on Artificial Intelligence and Image Segmentation.
Project Contributor for various AI-related projects including:
- Development of a Deep Learning CT Shortening Algorithm for Hyundai (2024 – Present)
- AI Pediatric Behavioral Analysis System for ASD (March 2023 – July 2023)
- Virtual-based Diet Assistant Application (March 2022 – November 2022)
- Participation in the AI Bookathon Competition (November 2021)

🏆 Achievements

Best Paper Award at the Spring Academic Conference (Korean Society for Emotion and Sensibility, 2023) for outstanding research contributions.

🏅 Awards and Honors

2023: Best Paper Award at the Spring Academic Conference, Korean Society for Emotion and Sensibility.

🛠️ Skills

Programming Languages: Python, LaTeX, Git, Android platforms
Machine Learning Tools: PyTorch, TensorFlow, scikit-learn

Publication Top Notes:

Latest research trends in open vocabulary segmentation based on visual-linguistic pre-learning models

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

Posted on 09/12/2024 by ScienceFather

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

Dr. Jinxin Cao | Computer Vision Award | Best Researcher Award

Posted on 17/08/2024 by ScienceFather

Dr. Jinxin Cao | Computer Vision Award | Best Researcher Award

Dr. Jinxin Cao, China University of Petroluem, Beijing, China

Jinxin Cao is a Doctor of Engineering and a PhD student at the China University of Petroleum, Beijing. Since joining the institution in August 2018, he has focused on the integration of artificial intelligence with energy and mining, specializing in computer vision in microfluidics, signal processing, and time series analysis. His research covers a broad spectrum, including tight oil development, microfluidics, interfacial mechanisms, and numerical simulation. Cao has led over 15 major projects, including special projects, joint fund integrations, and comprehensive scientific research initiatives. He has achieved significant breakthroughs in microfluidic image processing, elucidating interface evolution laws and mechanical mechanisms, which are pivotal for advancing “Lab on a Chip” technologies. Additionally, he has applied signal processing techniques to petroleum engineering, utilizing empirical mode decomposition and Hilbert-Huang transforms to analyze and predict oil well production. His contributions include 11 published papers (8 indexed by SCI/EI), 5 granted patents, and 6 accepted articles. Cao has also earned 20 awards in science, technology, and competitions, highlighting his impact in his field

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award:

Jinxin Cao is currently pursuing a PhD at China University of Petroleum, Beijing (CUPB) and has been a part of the institution since August 2018. His research focuses on artificial intelligence applications in petroleum engineering, including computer vision in microfluidics, signal processing, and time series analysis. With a total experience of 6 years at CUPB, he has made significant contributions to various interdisciplinary fields.

Education:

Doctor of Engineering
Institution: China University of Petroleum, Beijing
Specialization: Energy and Mining
Research Focus: Computer Vision in Microfluidics

Work Experience:

Position: Doctor of Engineering
Department: College of Petroleum Engineering
Institution: China University of Petroleum, Beijing
Duration: August 2018 – Present
Experience: Jinxin Cao has been engaged in artificial intelligence with a focus on computer vision in microchips, signal processing, time series processing, tight oil development, microfluidics, and interfacial mechanisms. He has been involved in over 15 major projects, including special projects, joint fund integration projects, and comprehensive scientific research endeavors. His work has led to significant breakthroughs in microfluidic image processing, uncovering interface evolution laws and mechanical mechanisms in microfluidic processes using computer vision methods. Additionally, Cao has applied signal processing techniques to petroleum engineering, utilizing empirical mode decomposition and Hilbert-Huang transform to analyze oil well production and predict future production using artificial intelligence methods.

Academic Achievements:

Publications: 11 academic papers, 8 indexed by SCI/EI
Patents: 5 invention patents
Accepted Articles: 6
Awards: 20 science and technology or competition awards at various levels