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Kim, Sungnyun
18  Ergebnisse:
Personensuche X
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1

STaR: Distilling Speech Temporal Relation for Lightweight S..:

, In: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
Jang, Kangwook ; Kim, Sungnyun ; Kim, Hoirin - p. 10721-10725 , 2024
Link: https://doi.org/10.1109/..
 
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2

Coreset Sampling from Open-Set for Fine-Grained Self-Superv..:

, In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR),
Kim, Sungnyun ; Bae, Sangmin ; Yun, Se-Young - p. 7537-7547 , 2023
Link: https://doi.org/10.1109/..
 
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3

Calibration of Few-Shot Classification Tasks: Mitigating Mi..:

Kim, Sungnyun ; Yun, Se-Young
IEEE Access.  10 (2022)  - p. 53894-53908 , 2022
Link: https://doi.org/10.1109/..
 
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4

ReFine: Re-randomization before Fine-tuning for Cross-domai..:

, In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management,
Oh, Jaehoon ; Kim, Sungnyun ; Ho, Namgyu... - p. 4359-4363 , 2022
Link: https://dl.acm.org/doi/1..
 
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5

Patch-Mix Contrastive Learning with Audio Spectrogram Trans..:

Bae, Sangmin ; Kim, June-Woo ; Cho, Won-Yang...
http://arxiv.org/abs/2305.14032.  , 2023
Link: http://arxiv.org/abs/230..
 
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6

Recycle-and-Distill: Universal Compression Strategy for Tra..:

Jang, Kangwook ; Kim, Sungnyun ; Yun, Se-Young.
http://arxiv.org/abs/2305.11685.  , 2023
Link: http://arxiv.org/abs/230..
 
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7

STaR: Distilling Speech Temporal Relation for Lightweight S..:

Jang, Kangwook ; Kim, Sungnyun ; Kim, Hoirin
http://arxiv.org/abs/2312.09040.  , 2023
Link: http://arxiv.org/abs/231..
 
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8

DiffBlender: Scalable and Composable Multimodal Text-to-Ima..:

Kim, Sungnyun ; Lee, Junsoo ; Hong, Kibeom..
http://arxiv.org/abs/2305.15194.  , 2023
Link: http://arxiv.org/abs/230..
 
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9

Coreset Sampling from Open-Set for Fine-Grained Self-Superv..:

Kim, Sungnyun ; Bae, Sangmin ; Yun, Se-Young
http://arxiv.org/abs/2303.11101.  , 2023
Link: http://arxiv.org/abs/230..
 
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10

Understanding Cross-Domain Few-Shot Learning Based on Domai..:

Oh, Jaehoon ; Kim, Sungnyun ; Ho, Namgyu...
http://arxiv.org/abs/2202.01339.  , 2022
Link: http://arxiv.org/abs/220..
 
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11

How to Fine-tune Models with Few Samples: Update, Data Augm..:

Kim, Yujin ; Oh, Jaehoon ; Kim, Sungnyun.
http://arxiv.org/abs/2205.07874.  , 2022
Link: http://arxiv.org/abs/220..
 
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12

ReFine: Re-randomization before Fine-tuning for Cross-domai..:

Oh, Jaehoon ; Kim, Sungnyun ; Ho, Namgyu...
http://arxiv.org/abs/2205.05282.  , 2022
Link: http://arxiv.org/abs/220..
 
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13

Self-Contrastive Learning: Single-viewed Supervised Contras..:

Bae, Sangmin ; Kim, Sungnyun ; Ko, Jongwoo...
http://arxiv.org/abs/2106.15499.  , 2021
Link: http://arxiv.org/abs/210..
 
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14

MixCo: Mix-up Contrastive Learning for Visual Representatio:

Kim, Sungnyun ; Lee, Gihun ; Bae, Sangmin.
http://arxiv.org/abs/2010.06300.  , 2020
Link: http://arxiv.org/abs/201..
 
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15

Calibration of Few-Shot Classification Tasks: Mitigating Mi..:

Sungnyun Kim ; Se-Young Yun
https://ieeexplore.ieee.org/document/9777704/.  , 2022
Link: https://doi.org/10.1109/..
 
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