Kang Ryoung Park
Papers
12
Total Citations
250
H-Index
8
About
Kang Ryoung Park is a prolific researcher whose work spans computer vision, deep learning, and intelligent robotics, with particular emphasis on semantic segmentation, autonomous systems, and AI-driven agricultural and medical imaging. His research has made meaningful contributions across remarkably diverse domains, demonstrating a rare ability to apply advanced neural network architectures to real-world challenges. Park's most-cited work, *LightDenseYOLO* (2018, 71 citations), introduced a fast and accurate marker-tracking system for autonomous UAV landing using visible-light cameras, offering a computationally efficient alternative to multi-sensor approaches. In medical imaging, his *DSRD-Net* and *CFFR-Net* frameworks address the complex task of surgical instrument segmentation in robot-assisted minimally invasive surgery, improving precision and patient safety. His contributions to gastrointestinal diagnostics include polyp detection and colorectal cancer classification using multi-scale feature aggregation networks. Beyond medicine, Park has advanced agricultural AI through plant disease classification, crop-weed segmentation, and motion deblurring systems, enabling smarter farming robotics. His work on skin segmentation and low-light image enhancement further demonstrates his breadth. Collectively accumulating over 240 citations, Park's research consistently bridges theoretical innovation with practical, high-impact applications across healthcare, agriculture, and autonomous systems.
Research Focus
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Top Papers
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