Personal profile
In Korean
김정홍 교수(IT대학 컴퓨터학부)
Education
o (2012) B.A., Kyungpook National University
o (2015) M.A., Kyungpook National University
o (2020) Ph.D., Chungnam National University
o (2015) M.A., Kyungpook National University
o (2020) Ph.D., Chungnam National University
Professional Experience
o (1988 ~ 1996) Senior Researcher, ETRI
o (1996 ~ 2008) Sangju National University
o (2008 ~ present) Kyungpook National University
o (1996 ~ 2008) Sangju National University
o (2008 ~ present) Kyungpook National University
Research Interests
Multimedia Information Processing, Computer vision using deep learning methods, Anomaly detection in image and video, Self-supervised learning image classification and visualization. Medical Image Segmentation.
Major Research Achievements
o Extensive knowledge distillation model: an end-to-end effective anomaly detection model for real-time industrial applications
o Consecutive multiscale feature learning-based image classification model
o Digital Twin Model: A Real-Time Emotion Recognition System for Personalized Healthcare
o An integrated mediapipe-optimized GRU model for Indian sign language recognition
o UzADL: Anomaly detection and localization using graph Laplacian matrix-based unsupervised learning method
o REF-Net: Robust, Efficient, and Fast Network for Semantic Segmentation Applications Using Devices With Limited Computational Resources
o FU-Net: Fast Biomedical Image Segmentation Model based on Bottleneck Convolution Layers
o Consecutive multiscale feature learning-based image classification model
o Digital Twin Model: A Real-Time Emotion Recognition System for Personalized Healthcare
o An integrated mediapipe-optimized GRU model for Indian sign language recognition
o UzADL: Anomaly detection and localization using graph Laplacian matrix-based unsupervised learning method
o REF-Net: Robust, Efficient, and Fast Network for Semantic Segmentation Applications Using Devices With Limited Computational Resources
o FU-Net: Fast Biomedical Image Segmentation Model based on Bottleneck Convolution Layers
url
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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A hybrid unsupervised-weakly supervised method for video anomaly detection
Rakhmonov, A. A. U., Varnousefaderani, B. A. & Kim, J., Sep 2025, In: Pattern Analysis and Applications. 28, 3, 135.Research output: Contribution to journal › Article › peer-review
2 Scopus citations -
Enforced clustering for zero-to-one-shot texture anomaly detection
Amirian Varnousefaderani, B., Rakhmonov, A. A. U., Kim, J. S. & Kim, J., May 2025, In: Machine Vision and Applications. 36, 3, 53.Research output: Contribution to journal › Article › peer-review
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Heuristic Weight Initialization for Transfer Learning in Classification Problems
Lolaev, M., Paul, A. & Kim, J., 2025, In: Computers, Materials and Continua. 85, 2, p. 4155-4171 17 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Real-time isolation of physiological tremor using recursive singular spectrum analysis and random vector functional link for surgical robotics
Rasheed, A., Kim, J., Ang, W. T. & Veluvolu, K. C., Mar 2025, In: ISA Transactions. 158, p. 556-571 16 p.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Telehealth 2.0: A Novel Framework for Real-Time Liveliness Detection and Mood Analysis
Subramanian, B., Ugliz, R. A. A., Varnousefaderani, B. A. & Kim, J., 2025, Advances in Intelligent Information Hiding and Multimedia Signal Processing, Volume 2 - Proceeding of the 19th International Conference on IIH-MSP in conjunction with 11th International Conference on Orange Technology, Applications and Tools. Tseng, S.-P., Paul, A., Pan, J.-S. & Favorskaya, M. (eds.). Springer Science and Business Media Deutschland GmbH, p. 149-159 11 p. (Smart Innovation, Systems and Technologies; vol. 416).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review