Technology Opportunity Discovery using Deep Learning-based Text Mining and a Knowledge Graph MyoungHoon Lee a 1, Suhyeon Kim a 1, Hangyeol Kim b, Junghye Lee c Abstract To capture emerging technologies in the fast-changing technology market, use of information concerning new technology-based firms (NTBFs) is strongly encouraged, in...
Quantifying incident impacts and identifying influential features in urban traffic networks AuthorLee, JuYeong; Kwak, JiIn; Oh, YongKyung; Kim, Sungil Abstract Traffic incidents are a common occurrence in urban traffic networks, but predicting their impacts is challenging because of network complexity and the dynamic spatial and temporal dependencies inherent in traffic data....
Risk score-embedded deep learning for biological age estimation: Development and validation Authors: Suhyeon Kim, Hangyeol Kim, Eun-Sol Lee, Chiehyeon Lim, Junghye Lee Authors Info & Claims Abstract The health index measures a person’s overall health status which provides useful information for people to manage their health, so developing a precise...
Driving Risk Assessment Using Non-Negative Matrix Factorization With Driving Behavior Records IEEE Transactions on Intelligent Transportation Systems ( IF 8.5 ) Pub Date: 2022-08-01 , DOI:10.1109/tits.2022.3193125 Hyunwoo Seo 1 , Jongkyung Shin 2 , Ki-Hun Kim 3 , Chiehyeon Lim 4 , Jungcheol Bae 5 Affiliations Aggressive driving behavior (ADB) is a major cause of traffic accidents. As ADB is controllable, ADB-based driving risk assessment is an effective method...
Abstract Quantization is a very effective optimization technique to reduce hardware cost and memory footprint of deep neural network (DNN) accelerators. In particular, post-training quantization (PTQ) is often preferred as it does not require a full dataset or costly retraining. However, performance of PTQ lags significantly...
S2Contact: Graph-based Network for 3D Hand-Object Contact Estimation with Semi-Supervised Learning Tze Ho Elden Tse, Zhongqun Zhang, Kwang In Kim, Ales Leonardis, Feng Zheng, Hyung Jin Chang Despite the recent efforts in accurate 3D annotations in hand and object datasets, there still exist gaps in 3D hand and object reconstructions. Existing works...
Multi-Person 3D Pose and Shape Estimation via Inverse Kinematics and Refinement Junuk Cha, Muhammad Saqlain, GeonU Kim, Mingyu Shin, Seungryul Baek Estimating 3D poses and shapes in the form of meshes from monocular RGB images is challenging. Obviously, it is more difficult than estimating 3D poses only in the form of...
Zero-Shot Learning for Reflection Removal of Single 360-Degree Image Abstract The existing methods for reflection removal mainly focus on removing blurry and weak reflection artifacts and thus often fail to work with severe and strong reflection artifacts. However, in many cases, real reflection artifacts are sharp and intensive enough...
Connecting Low-Loss Subspace for Personalized Federated Learning Seok-Ju Hahn, Minwoo Jeong, Junghye Lee Due to the curse of statistical heterogeneity across clients, adopting a personalized federated learning method has become an essential choice for the successful deployment of federated learning-based services. Among diverse branches of personalization techniques, a model...
Recommendation in Offline Stores Title Recommendation in Offline Stores Author Shin, Jongkyung; Lee, Changhun; Lim, Chiehyeon; Shin, Yunmo; Lim, Junseok Issue Date 2022-08-18 Publisher ACM Citation International Conference on Knowledge Discovery and Data Mining Abstract With the current advancements in mobile and sensing technologies used to collect real-time data...
