31 citations · 92 across the 12 of their papers we have counts for
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cs.SD2022★ 7 cited
Exploring Train and Test-Time Augmentations for Audio-Language Learning
Eungbeom Kim, Jinhee Kim, Yoori Oh +5
In this paper, we aim to unveil the impact of data augmentation in audio-language multi-modal learning, which has not been explored despite its importance. We explore various augme…
cs.LG2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
SungYub Kim, Sihwan Park, Kyungsu Kim +1
Explaining generalizations and preventing over-confident predictions are central goals of studies on the loss landscape of neural networks. Flatness, defined as loss invariability…
cs.CV2022★ 2 cited
RecurSeed and EdgePredictMix: Pseudo-Label Refinement Learning for Weakly Supervised Semantic Segmentation across Single- and Multi-Stage Frameworks
Sanghyun Jo, In-Jae Yu, Kyungsu Kim
Although weakly supervised semantic segmentation using only image-level labels (WSSS-IL) is potentially useful, its low performance and implementation complexity still limit its ap…