1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2021
Attribution Mask: Filtering Out Irrelevant Features By Recursively Focusing Attention on Inputs of DNNs
Jae-Hong Lee, Joon-Hyuk Chang
Attribution methods calculate attributions that visually explain the predictions of deep neural networks (DNNs) by highlighting important parts of the input features. In particular…
cs.CV2019★ 1 cited
Photometric Transformer Networks and Label Adjustment for Breast Density Prediction
Jaehwan Lee, Donggeon Yoo, Jung Yin Huh +1
Grading breast density is highly sensitive to normalization settings of digital mammogram as the density is tightly correlated with the distribution of pixel intensity. Also, the g…
cs.CV2018
Keep and Learn: Continual Learning by Constraining the Latent Space for Knowledge Preservation in Neural Networks
Hyo-Eun Kim, Seungwook Kim, Jaehwan Lee
Data is one of the most important factors in machine learning. However, even if we have high-quality data, there is a situation in which access to the data is restricted. For examp…