Multi-class Multi-object Tracking Using Changing Point Detection. - Byungjae Lee; Enkhbayar Erdenee; SongGuo Jin; Mi Young Nam; Young Giu Jung; Phill-Kyu Rhee (ECCV Workshops (2), 2016)

Multi-Class Multi-Object Tracking using Changing Point Detection. - Byungjae Lee; Enkhbayar Erdenee; SongGuo Jin; Phill-Kyu Rhee (CoRR, 2016)

Efficient object detection using convolutional neural network-based hierarchical feature modeling. - Byungjae Lee; Enkhbayar Erdenee; SongGuo Jin; Phill-Kyu Rhee (Signal Image Video Process., 2016)

A Robust and Effective Approach Towards Accurate Metastasis Detection and pN-stage Classification in Breast Cancer. - Byungjae Lee; Kyunghyun Paeng (MICCAI (2), 2018)

From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge. - Péter Bándi; Oscar Geessink; Quirine Manson; Marcory Van Dijk; Maschenka Balkenhol; Meyke Hermsen; Babak Ehteshami Bejnordi; Byungjae Lee; Kyunghyun Paeng; Aoxiao Zhong; Quanzheng Li; Farhad Ghazvinian Zanjani; et al. (IEEE Trans. Medical Imaging, 2019)

Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images - the ACDC@LungHP Challenge 2019. - Zhang Li; Jiehua Zhang; Tao Tan 002; Xichao Teng; Xiaoliang Sun; Yang Li 058; Lihong Liu; Yang Xiao; Byungjae Lee; Yilong Li; Qianni Zhang; Shujiao Sun; et al. (CoRR, 2020)

Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images - The ACDC@LungHP Challenge 2019. - Zhang Li; Jiehua Zhang; Tao Tan 002; Xichao Teng; Xiaoliang Sun; Hong Zhao; Lihong Liu; Yang Xiao; Byungjae Lee; Yilong Li; Qianni Zhang; Shujiao Sun; et al. (IEEE J. Biomed. Health Informatics, 2021)

LightTrader : World's first AI-enabled High-Frequency Trading Solution with 16 TFLOPS / 64 TOPS Deep Learning Inference Accelerators. - Hyunsung Kim 003; Sungyeob Yoo; Jaewan Bae; Kyeongryeol Bong; Yoonho Boo; Karim Charfi; Hyo-Eun Kim; Hyun Suk Kim; Jinseok Kim 006; Byungjae Lee; Jaehwan Lee; Myeongbo Shim; et al. (HCS, 2022)

2.4 ATOMUS: A 5nm 32TFLOPS/128TOPS ML System-on-Chip for Latency Critical Applications. - Chang-Hyo Yu; Hyo-Eun Kim; Sungho Shin; Kyeongryeol Bong; Hyunsuk Kim; Yoonho Boo; Jaewan Bae; Minjae Kwon; Karim Charfi; Jinseok Kim 006; Hongyun Kim; Myeongbo Shim; et al. (ISSCC, 2024)