2020.03 ~ : Assistant Professor, Sangmyung University - https://www.smu.ac.kr
2018.12 ~ 2020.03 : Korea Aerospace Research Institute (KARI) - https://www.kari.re.kr
2014.09 ~ 2019.02 : School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST) Video and Image Computing Lab. (VICLab) - https://www.viclab.kaist.ac.kr
E-mail : yongwoo.kim@smu.ac.kr or yongwoo.kim@kaist.ac.kr
CV in PDF
LinkedIn : https://www.linkedin.com/in/yongwookim85
Hardware Architecture for deep-learning : Low complexity, low power applications
Hardware Logic design for image/video processing/compression algorithms
Low level vision - Super-Resolution, Segmentation
Computer Vision - Object detection
High speed serial interface - DisplayPort (with eDP), HDMI, VbyOne
Lee, J. C., Yoo, J., Kim, Yongwoo, Moon, S., & Ko, J. H. (2021). Robust detection of small and dense objects in images from autonomous aerial vehicles. Electronics Letters, 57(16), 611-613. https://doi.org/10.1049/ell2.12245.
Choi, Y.; Han, S.; Kim, Yongwoo. A No-Reference CNN-Based Super-Resolution Method for KOMPSAT-3 Using Adaptive Image Quality Modification. Remote Sens. 2021, 13, 3301, https://doi.org/10.3390/rs13163301.
J. Kim, J. -K. Kang and Yongwoo. Kim, "A Resource Efficient Integer-Arithmetic-Only FPGA-Based CNN Accelerator for Real-Time Facial Emotion Recognition," in IEEE Access, vol. 9, pp. 104367-104381, 2021, https://doi.org/10.1109/ACCESS.2021.3099075.
Lee, J. C., Yoo, J., Kim, Yongwoo., Moon, S., & Ko, J. H, "Robust detection of small and dense objects in images from autonomous aerial vehicles," Electronics Letters. - http://doi.org/10.1049/ell2.12245
Jae-J. Choi, Yongwoo Kim and M. Kim, "S3: A Spectral-Spatial Structure Loss for Pan-Sharpening Networks," in IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 5, pp. 829-833, May 2020, doi: 10.1109/LGRS.2019.2934493.
Yongwoo Kim, Jae-Seok Choi and Munchurl Kim, "A Real-Time Convolutional Neural Network for Super-Resolution on FPGA with Applications to 4K UHD 60 fps Video Services," IEEE Transactions on Circuits and Systems for Video Technology, vol. 29, no. 8, pp. 2521-2534, Aug. 2019. - https://doi.org/10.1109/TCSVT.2018.2864321
Yongwoo Kim, Jae-Seok Choi and Munchurl Kim, "2X Super-Resolution Hardware using Edge-Orientation-based Linear Mapping for Real-Time 4K UHD 60 fps Video Applications," IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 65, no. 9, pp. 1274-1278, Sept. 2018. - http://ieeexplore.ieee.org/document/8274961
Yong-Woo Kim, Beomseok Shin, Jin-Ku Kang, "High-speed 8B/10B encoder design using a simplified coding table," IEICE Electronics Express, vol. 5, Issue 16, pp. 581-585, 2008 - https://doi.org/10.1587/elex.5.581
Y. Choi and Yongwoo. Kim, "A No-Reference Super Resolution for Satellite Image Quality Enhancement for KOMPSAT-3," IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020, pp. 220-223, https://doi.org/10.1109/IGARSS39084.2020.9324422.
Du D. , Yongwoo Kim, et al. (2020) VisDrone-DET2020: The Vision Meets Drone Object Detection in Image Challenge Results. In: Bartoli A., Fusiello A. (eds) Computer Vision – ECCV 2020 Workshops. ECCV 2020. Lecture Notes in Computer Science, vol 12538. Springer, Cham. https://doi.org/10.1007/978-3-030-66823-5_42
Muqeet, A., Hwang, J., Yang, S., Kang, J. H., Kim, Y., & Bae, S. H. (2020). Ultra lightweight image super-resolution with multi-attention layers. arXiv preprint arXiv:2008.12912.
KIM, Yongwoo, et al. A CNN-Based Multi-scale Super-Resolution Architecture on FPGA for 4K/8K UHD Applications. In: International Conference on Multimedia Modeling. Springer, Cham, 2020. p. 739-744.
Ignatov, A., Timofte, ..., Yongwoo Kim, ..., R., Van Vu, T., Luu, T. M., Pham, T. X., Van Nguyen, C., ... & Ran, J. (2018). Pirm challenge on perceptual image enhancement on smartphones: Report. arXiv preprint arXiv:1810.01641.
Yong-woo Kim, Jin-Ku Kang, "An 8B/10B encoder with a modified coding table," Circuits and Systems, 2008. APCCAS 2008. IEEE Asia Pacific Conference, pp. 1422-1525, Nov. 2008. - http://ieeexplore.ieee.org/abstract/document/4746322
Yong-woo Kim, Seong-bok Cha, Jin-ku Kang, "A design of DisplayPort link layer," SoC Design Conference, 2008. ISOCC'08. International, vol. 2, pp.45-48, Nov. 2008 - http://ieeexplore.ieee.org/abstract/document/4815680
전지훈, 김재명, 강진구, & 김용우. (2022). 임베디드 시스템에서의 객체 탐지 네트워크 추론 가속을 위한 필터 가지치기 기법 연구. 전자공학회논문지, 59(3), 69-77.
강태운, & 김용우. (2022). 젯슨 나노를 이용한 심층 컨볼루션 신경망 기반 실시간 마스크 착용 검출기 구현. 한국산학기술학회 논문지, 23(1), 652-659.
김재명, 강진구, and 김용우. "얼굴 감정인식을 위한 양자화된 경량 합성곱 신경망 구조 연구." 전자공학회논문지 57.12 (2020): 51-59.
김재명, and 김용우. "정수 연산만을 사용하는 하드웨어 친화적인 양자화된 CNN 구현." 전자공학회논문지 57.12 (2020): 60-69.
최연주, 김민식, 김용우, & 한상혁. (2020). 원격 탐사 영상을 활용한 CNN 기반의 초해상화 기법 연구. 대한원격탐사학회지, 36(3), 449-460.
Kim, Yongwoo, and Jonghwan Lee. "Quantized CNN-based Super-Resolution Method for Compressed Image Reconstruction." Journal of the Semiconductor & Display Technology 19.4 (2020): 71-76.
Kim, Yongwoo, and Jonghwan Lee. "Machine Learning Model for Low Frequency Noise and Bias Temperature Instability." Journal of the Semiconductor & Display Technology 19.4 (2020): 88-93.
한상혁, 김용우, et al. "딥러닝 기반 SAR 영상 변화 탐지 기술 동향." 항공우주산업기술동향 17.1 (2019): 104-112.
김재명, 강진구, 김용우. 얼굴 감정인식을 위한 양자화된 경량 합성곱 신경망 구조 연구. 전자공학회논문지, 2020, 57.12: 51-59.
김용우, 김진형. 큐브위성용 온보드 컴퓨터에서의 딥러닝 알고리즘 개발 환경 구축. 한국항공우주학회 학술발표회 초록집, 2019, 175-176.
유은지, 이강규, 최연주, 김용우, & 김종옥. (2019). 다해상도 위성영상 초해상도를 위한 역투영 피라미드 모델. 한국항공우주학회 학술발표회 초록집, 184-185.
최연주, 김용우. 딥러닝 기술 기반 아리랑 위성 영상 해상도 향상 연구. 한국항공우주학회 학술발표회 초록집, 2019, 186-187.
김용우, 최재석, 최연주, & 한상혁. (2019). CNN 기반 KOMPSAT-3 위성 영상 Pan Sharpening 알고리즘 연구. 한국항공우주학회 학술발표회 초록집, 518-519.
최재석, 김용우, 김문철, 최연주, & 한상혁. (2018). SpaceNet 위성영상을 이용한 딥러닝 기반 초해상화 연구. 한국항공우주학회 학술발표회 초록집, 396-397.
US
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US20210065334A1 (Pending), Image processing method and device using feature map compression
US20210082087A1 (Pending), Image pipeline processing method and device
US10664961B2, Inverse tone mapping method
US9286841B2, Embedded DisplayPort system and method for controlling panel self refresh mode
AU
AU2018102147A4, Method and apparatus for super-resolution using line unit operation
KR
KR102017998B1, A method and apparatus of image pipeline processing
KR102017995B1, A method and apparatus of super resolution using line unit operation
KR102017996B1, A method and apparatus of image processing using line input and ouput
KR102017997B1, A method and apparatus of image processing using feature map compression
Korea Aerospace Research Institute (KARI), Jun. 2018 – Dec. 2018
role : project co-lead
description : satellite super resolution
Samsung Electronics Co., Ltd., Apr. 2018 – Dec. 2018
role : project co-lead
description : perceptual super resolution
National Research Foundation of Korea, Aug. 2017 – Dec. 2018
role : deep-learning research - low complexity CNN-based Super Resolution
description : low complexity CNN-based Super Resolution on FPGA
PIXELPLUS Co. Ltd., Jan. 2018 – Dec. 2018
role : project co-lead
description : CNN-based demosaicking algorithm design
B.S. in Electronic Engineering, Inha University, Incheon, Korea, Mar.2003 - Feb. 2007 (GPA : 4.22 / 4.50)
M.S. in Electronic Engineering, Inha University, Incheon, Korea, Mar.2007 - Feb. 2009 (GPA : 4.44 / 4.50)
Ph.D. in Electrical Engineering, KAIST, Daejeon, Korea, Sep. 2014 - Feb. 2019 (GPA : 3.45 / 4.20)
Hardware Architecture for Deep learning/Machine learning
Logic design for Image/Video processing/compression algorithms
High-speed serial interface (Inter-module : eDP, Vx1 and HDMI, Intra-panel : CEDS)
ASIC Logic Design for optimizing power, speed
FPGA Board Design & verification
Physical layer for logic (8B/10B encoder, scrambler), Link layer IP for eDP/DP serial I/F design
Memory Controller Design (DDR-1,2,3, LPDDR-1,2)
Deep Learning Framework - Pytorch, tensorflow, Caffe
Hardware Description Languages - Verilog, SystemVerilog
Verification Methodology - UVM
Synopsys Tool - Design Compiler (Synthesis), DFT Compiler (DFT), TetraMax (ATPG), PrimeTime (STA), VCS (Logic Simulator), synplify (FPGA synthesis), Novas Verdi & Debussy (Total Debugging Solution), Spyglass (Lint, CDC, Power Analysis)
Cadence Tool - NC-Verilog (Logic Simulator)
Mentor Tool - Modelsim & Questasim (Logic Simulator)
Scripting Languages - Tcl/tk, Python, Linux Shell Programming (bash, csh)
Programming Languages - C, C++, Visual C++ (MFC)
FPGA Tool - Xilinx – ISE, Vivado, Altera – Quartus
Board PCB Design - Schematic : OrCAD (Allegro)