30 citations · 173 across the 35 of their papers we have counts for
9 papers · 1 filter
Adverse Weather Image Translation with Asymmetric and Uncertainty-aware GAN
Jeong-gi Kwak, Youngsaeng Jin, Yuanming Li +3
Adverse weather image translation belongs to the unsupervised image-to-image (I2I) translation task which aims to transfer adverse condition domain (eg, rainy night) to standard do…
Action Recognition with Domain Invariant Features of Skeleton Image
Han Chen, Yifan Jiang, Hanseok Ko
Due to the fast processing-speed and robustness it can achieve, skeleton-based action recognition has recently received the attention of the computer vision community. The recent C…
A Teacher-Student Framework with Fourier Augmentation for COVID-19 Infection Segmentation in CT Images
Han Chen, Yifan Jiang, Hanseok Ko +1
Automatic segmentation of infected regions in computed tomography (CT) images is necessary for the initial diagnosis of COVID-19. Deep-learning-based methods have the potential to…
A Lightweight dynamic filter for keyword spotting
Donghyeon Kim, Kyungdeuk Ko, Jeonggi Kwak +2
Keyword Spotting (KWS) from speech signals is widely applied to perform fully hands-free speech recognition. The KWS network is designed as a small-footprint model so it can contin…
Memory-based Semantic Segmentation for Off-road Unstructured Natural Environments
Youngsaeng Jin, David K. Han, Hanseok Ko
With the availability of many datasets tailored for autonomous driving in real-world urban scenes, semantic segmentation for urban driving scenes achieves significant progress. How…
SpecMix : A Mixed Sample Data Augmentation method for Training withTime-Frequency Domain Features
Gwantae Kim, David K. Han, Hanseok Ko
A mixed sample data augmentation strategy is proposed to enhance the performance of models on audio scene classification, sound event classification, and speech enhancement tasks.…
CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects
Ange Lou, Shuyue Guan, Hanseok Ko +1
Segmenting medical images accurately and reliably is important for disease diagnosis and treatment. It is a challenging task because of the wide variety of objects' sizes, shapes,…
CPNet: Cross-Parallel Network for Efficient Anomaly Detection
Youngsaeng Jin, Jonghwan Hong, David Han +1
Anomaly detection in video streams is a challenging problem because of the scarcity of abnormal events and the difficulty of accurately annotating them. To alleviate these issues,…
Few-shot Learning for CT Scan based COVID-19 Diagnosis
Yifan Jiang, Han Chen, David K. Han +1
Coronavirus disease 2019 (COVID-19) is a Public Health Emergency of International Concern infecting more than 40 million people across 188 countries and territories. Chest computed…