58 citations · 93 across the 9 of their papers we have counts for
4 papers · 1 filter
Adversarial Defense by Suppressing High-frequency Components
Zhendong Zhang, Cheolkon Jung, Xiaolong Liang
Recent works show that deep neural networks trained on image classification dataset bias towards textures. Those models are easily fooled by applying small high-frequency perturbat…
GBDT-MO: Gradient Boosted Decision Trees for Multiple Outputs
Zhendong Zhang, Cheolkon Jung
Gradient boosted decision trees (GBDTs) are widely used in machine learning, and the output of current GBDT implementations is a single variable. When there are multiple outputs, G…
Attention-Aware Linear Depthwise Convolution for Single Image Super-Resolution
Seongmin Hwang, Gwanghuyn Yu, Cheolkon Jung +1
Although deep convolutional neural networks (CNNs) have obtained outstanding performance in image superresolution (SR), their computational cost increases geometrically as CNN mode…
Recurrent Convolution for Compact and Cost-Adjustable Neural Networks: An Empirical Study
Zhendong Zhang, Cheolkon Jung
Recurrent convolution (RC) shares the same convolutional kernels and unrolls them multiple steps, which is originally proposed to model time-space signals. We argue that RC can be…