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Jae-Hyeok Lee 0001
Person information
- affiliation: Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea
Other persons with the same name
- Jae-Hyeok Lee
- Jae-Hyeok Lee 0002 — Pusan National University Yangsan Hospital, Yangsan, Korea
- Jae-Hyeok Lee 0003 — Korea University, Seoul, Korea
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2020 – today
- 2024
- [j6]Gyeongdo Ham
, Yucheol Cho
Difficulty level-based knowledge distillation. Neurocomputing 606: 128375 (2024) - 2023
- [j5]Yucheol Cho
Ambiguity-aware robust teacher (ART): Enhanced self-knowledge distillation framework with pruned teacher network. Pattern Recognit. 140: 109541 (2023) - [c5]Jae-Hyeok Lee, Dae-Shik Kim:
ICE-NeRF: Interactive Color Editing of NeRFs via Decomposition-Aware Weight Optimization. ICCV 2023: 3468-3478 - [i2]Gyeongdo Ham, Seonghak Kim, Suin Lee, Jae-Hyeok Lee, Daeshik Kim:
Cosine Similarity Knowledge Distillation for Individual Class Information Transfer. CoRR abs/2311.14307 (2023) - 2022
- [j4]Gyeongdo Ham
P-PseudoLabel: Enhanced Pseudo-Labeling Framework With Network Pruning in Semi-Supervised Learning. IEEE Access 10: 115652-115662 (2022) - [j3]Ji-Man Yu, Gyeongdo Ham, Chungryeol Lee, Jae-Hyeok Lee, Joon-Kyu Han, Jin-Ki Kim, Donggon Jang, Nahyun Kim, Moon-Seok Kim, Sung Gap Im, Dae-Shik Kim, Yang-Kyu Choi
A Multiple-State Ion Synaptic Transistor Applicable to Abnormal Car Detection with Transfer Learning. Adv. Intell. Syst. 4(6) (2022) - 2020
- [j2]Jae-Hyeok Lee
MCSIP Net: Multichannel Satellite Image Prediction via Deep Neural Network. IEEE Trans. Geosci. Remote. Sens. 58(3): 2212-2224 (2020)
2010 – 2019
- 2019
- [c4]Jae-Hyeok Lee, Seong Tae Kim
Probenet: Probing Deep Networks. ICIP 2019: 3821-3825 - [c3]Seong Tae Kim
Visual evidence for interpreting diagnostic decision of deep neural network in computer-aided diagnosis. Computer-Aided Diagnosis 2019: 109500K - [c2]Hakmin Lee, Seong Tae Kim
Realistic Breast Mass Generation Through BIRADS Category. MICCAI (6) 2019: 703-711 - 2018
- [j1]Jeong-Chan Jin, Jae-Hyeok Lee, Eun-Sil Kim, Young-Jin Kim:
OPT: optimal human visual system-aware and power-saving color transformation for mobile AMOLED displays. Multim. Tools Appl. 77(13): 16699-16720 (2018) - [c1]Jae-Hyeok Lee, Seong Tae Kim
Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation. ECCV Workshops (6) 2018: 326-334 - [i1]Jae-Hyeok Lee, Seong Tae Kim, Hakmin Lee, Yong Man Ro:
Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation. CoRR abs/1809.06147 (2018)
Coauthor Index
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