7 citations · 19 across the 24 of their papers we have counts for
4 papers · 1 filter
Stochastic Subsampling With Average Pooling
Bum Jun Kim, Sang Woo Kim
Regularization of deep neural networks has been an important issue to achieve higher generalization performance without overfitting problems. Although the popular method of Dropout…
The Disappearance of Timestep Embedding in Modern Time-Dependent Neural Networks
Bum Jun Kim, Yoshinobu Kawahara, Sang Woo Kim
Dynamical systems are often time-varying, whose modeling requires a function that evolves with respect to time. Recent studies such as the neural ordinary differential equation pro…
Configuring Data Augmentations to Reduce Variance Shift in Positional Embedding of Vision Transformers
Bum Jun Kim, Sang Woo Kim
Vision transformers (ViTs) have demonstrated remarkable performance in a variety of vision tasks. Despite their promising capabilities, training a ViT requires a large amount of di…
Scale Equalization for Multi-Level Feature Fusion
Bum Jun Kim, Sang Woo Kim
Deep neural networks have exhibited remarkable performance in a variety of computer vision fields, especially in semantic segmentation tasks. Their success is often attributed to m…