8 citations · 25 across the 5 of their papers we have counts for
5 papers
Network Quantization with Element-wise Gradient Scaling
Junghyup Lee, Dohyung Kim, Bumsub Ham
Network quantization aims at reducing bit-widths of weights and/or activations, particularly important for implementing deep neural networks with limited hardware resources. Most m…
VOTE400(Voide Of The Elderly 400 Hours): A Speech Dataset to Study Voice Interface for Elderly-Care
Minsu Jang, Sangwon Seo, Dohyung Kim +3
This paper introduces a large-scale Korean speech dataset, called VOTE400, that can be used for analyzing and recognizing voices of the elderly people. The dataset includes about 3…
Learning with Privileged Information for Efficient Image Super-Resolution
Wonkyung Lee, Junghyup Lee, Dohyung Kim +1
Convolutional neural networks (CNNs) have allowed remarkable advances in single image super-resolution (SISR) over the last decade. Most SR methods based on CNNs have focused on ac…
ETRI-Activity3D: A Large-Scale RGB-D Dataset for Robots to Recognize Daily Activities of the Elderly
Jinhyeok Jang, Dohyung Kim, Cheonshu Park +3
Deep learning, based on which many modern algorithms operate, is well known to be data-hungry. In particular, the datasets appropriate for the intended application are difficult to…
Squeezed Convolutional Variational AutoEncoder for Unsupervised Anomaly Detection in Edge Device Industrial Internet of Things
Dohyung Kim, Hyochang Yang, Minki Chung +1
In this paper, we propose Squeezed Convolutional Variational AutoEncoder (SCVAE) for anomaly detection in time series data for Edge Computing in Industrial Internet of Things (IIoT…