Research output per year
Research output per year
Personal profile
In Korean
조대웅 교수(IT대학 전자공학부)
Education
o B.S., Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
o Ph.D., Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea (Integrated Ph.D. program)
o Ph.D., Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea (Integrated Ph.D. program)
Professional Experience
o Assistant Professor, Kyungpook National University, Korea
o Staff Engineer in Samsung Advanced Institute of Technology (SAIT), Samsung Electronics
o Staff Engineer in Samsung Advanced Institute of Technology (SAIT), Samsung Electronics
Research Interests
Deep Learning, Machine Learning, Computer Vision, Multi-Modal Learning, Causal Learning, Autonomous Driving, World Model, Deep Learning for Medical Data.
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Dive into the research topics where Dae Ung Jo is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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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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C2I-CAT: Class-to-Image Cross Attention Transformer for Out-of-Distribution Detection
Chung, J., Cho, S., Choi, H., Jo, D., Jung, Y. & Young Choi, J., 2024, In: IEEE Access. 12, p. 62793-62803 11 p.Research output: Contribution to journal › Article › peer-review
Open Access -
STXD: Structural and Temporal Cross-Modal Distillation for Multi-View 3D Object Detection
Jang, S., Jo, D. U., Hwang, S. J., Lee, D. & Ji, D., 2023, Advances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023. Oh, A., Neumann, T., Globerson, A., Saenko, K., Hardt, M. & Levine, S. (eds.). Neural information processing systems foundation, (Advances in Neural Information Processing Systems; vol. 36).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
2 Scopus citations -
Congestion-Aware Bayesian Loss for Crowd Counting
Jeong, J., Choi, J., Jo, D. U. & Choi, J. Y., 2022, In: IEEE Access. 10, p. 8462-8473 12 p.Research output: Contribution to journal › Article › peer-review
Open Access7 Scopus citations -
How Much a Model be Trained by Passive Learning Before Active Learning?
Jo, D. U., Yun, S. & Choi, J. Y., 2022, In: IEEE Access. 10, p. 34677-34689 13 p.Research output: Contribution to journal › Article › peer-review
Open Access2 Scopus citations -
Class-Attentive Diffusion Network for Semi-Supervised Classification
Lim, J., Um, D., Chang, H. J., Jo, D. U. & Choi, J. Y., 2021, 35th AAAI Conference on Artificial Intelligence, AAAI 2021. Association for the Advancement of Artificial Intelligence, p. 8601-8609 9 p. (35th AAAI Conference on Artificial Intelligence, AAAI 2021; vol. 10A).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access8 Scopus citations