4 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.CV2024
EQ-CBM: A Probabilistic Concept Bottleneck with Energy-based Models and Quantized Vectors
Sangwon Kim, Dasom Ahn, Byoung Chul Ko +2
The demand for reliable AI systems has intensified the need for interpretable deep neural networks. Concept bottleneck models (CBMs) have gained attention as an effective approach…
cs.CV2022★ 4 cited
STAR-Transformer: A Spatio-temporal Cross Attention Transformer for Human Action Recognition
Dasom Ahn, Sangwon Kim, Hyunsu Hong +1
In action recognition, although the combination of spatio-temporal videos and skeleton features can improve the recognition performance, a separate model and balancing feature repr…
cs.AI2020
Interpretation and Simplification of Deep Forest
Sangwon Kim, Mira Jeong, Byoung Chul Ko
This paper proposes a new method for interpreting and simplifying a black box model of a deep random forest (RF) using a proposed rule elimination. In deep RF, a large number of de…