162 citations · 303 across the 20 of their papers we have counts for
4 papers · 1 filter
Less-forgetful Learning for Domain Expansion in Deep Neural Networks
Heechul Jung, Jeongwoo Ju, Minju Jung +1
Expanding the domain that deep neural network has already learned without accessing old domain data is a challenging task because deep neural networks forget previously learned inf…
Why Do Deep Neural Networks Still Not Recognize These Images?: A Qualitative Analysis on Failure Cases of ImageNet Classification
Han S. Lee, Alex A. Agarwal, Junmo Kim
In a recent decade, ImageNet has become the most notable and powerful benchmark database in computer vision and machine learning community. As ImageNet has emerged as a representat…
Active Convolution: Learning the Shape of Convolution for Image Classification
Yunho Jeon, Junmo Kim
In recent years, deep learning has achieved great success in many computer vision applications. Convolutional neural networks (CNNs) have lately emerged as a major approach to imag…
Mimicking Ensemble Learning with Deep Branched Networks
Byungju Kim, Youngsoo Kim, Yeakang Lee +1
This paper proposes a branched residual network for image classification. It is known that high-level features of deep neural network are more representative than lower-level featu…