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- Tae-Seong Kim 0001
Kyung Hee University, Department of Biomedical Engineering, Korea - Tae-Seong Kim — disambiguation page
aka: Tae Seong Kim - Taeseong Kim
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Publication search results
found 119 matches
- 2023
- Min Keun Cho, Tae-Seon Kim:
Canine Biometric Identification Using ECG Signals and CNN-LSTM Neural Networks. IEEE Access 11: 145732-145746 (2023) - Ji-Soo Chang, Eunsang Jang, Youngkil Choi, Moonkyu Song, Sanghyo Lee, Gi-Jin Kang, Junho Kim, Uijong Song, Chang-Yeon Cho, Giyeong Ko, Hyunseok Hwang, Junseo Lee, Han-Sol Lee, Yong-Il Kwon, Kyungduck Seo, Taeseon Kim, Hyun-Wook Lim, Seongwook Song, Jae-Youl Lee, Sung-Ung Kwak:
A 1.05-A/m Minimum Magnetic Field Strength Single-Chip, Fully Integrated Biometric Smart Card SoC Achieving 792.5-ms Transaction Time With Anti-Spoofing Fingerprint Authentication. IEEE J. Solid State Circuits 58(1): 155-166 (2023) - Ismael Espinoza Jaramillo, Channabasava Chola, Jin Gyun Jeong, Ji-Heon Oh, Hwanseok Jung, Jin-Hyuk Lee, Won Hee Lee, Tae-Seong Kim:
Human Activity Prediction Based on Forecasted IMU Activity Signals by Sequence-to-Sequence Deep Neural Networks. Sensors 23(14): 6491 (2023) - Seung-Hyun Kong, Sang Jae Cho, Taeseon Kim, Sanguk Lee:
Stepped-Frequency Binary Offset Carrier Modulation for Global Navigation Satellite Systems. IEEE Trans. Aerosp. Electron. Syst. 59(3): 2733-2751 (2023) - Jin Gyun Jeong, Ji-Heon Oh, Hwanseok Jung, Jin Hyuk Lee, Ismael Nicolas Espinoza Jaramillo, Channabasava Chola, Won Hee Lee, Tae-Seong Kim:
Long-Horizon Manipulation by a Single-arm Robot via Sub-goal Network based Hierarchical Reinforcement Learning. ICBET 2023: 88-92 - SungHwan Moon, Tae Seong Kim, Jihye Ryu, Won Hee Lee:
Federated Learning for Sleep Stage Classification on Edge Devices via a Model-Agnostic Meta-Learning-Based Pre-Trained Model. ICCE-Berlin 2023: 188-192 - Daehyun Kwon, Heon Su Jeong, Jaemin Choi, Wijong Kim, Jae Woong Kim, Junsub Yoon, Jungmin Choi, Sanguk Lee, Hyunsub Norbert Rie, Jin-Il Lee, Jongbum Lee, Taeseong Jang, JunHyung Kim, Sanghee Kang, Jung-Bum Shin, Yanggyoon Loh, Chang-Yong Lee, Junmyung Woo, Hye-Seung Yu, Changhyun Bae, Reum Oh, Young-Soo Sohn, Changsik Yoo, Jooyoung Lee:
A 1.1V 6.4Gb/s/pin 24-Gb DDR5 SDRAM with a Highly-Accurate Duty Corrector and NBTI-Tolerant DLL. ISSCC 2023: 412-413 - Jung Hee Cheon, Minsik Kang, Taeseong Kim, Junyoung Jung, Yongdong Yeo:
High-Throughput Deep Convolutional Neural Networks on Fully Homomorphic Encryption Using Channel-By-Channel Packing. IACR Cryptol. ePrint Arch. 2023: 632 (2023) - 2022
- Duk-Min Kim, Yongchan Kim, Tae-Seong Roh, Hyoung Jin Lee:
Observation of unsteady motion induced by counterflow jet on blunt body in hypersonic flow. J. Vis. 25(1): 1-14 (2022) - Ismael Espinoza Jaramillo, Jin Gyun Jeong, Patricio Rivera Lopez, Choong-Ho Lee, Do-Yeon Kang, Tae-Jun Ha, Ji-Heon Oh, Hwanseok Jung, Jin Hyuk Lee, Won Hee Lee, Tae-Seong Kim:
Real-Time Human Activity Recognition with IMU and Encoder Sensors in Wearable Exoskeleton Robot via Deep Learning Networks. Sensors 22(24): 9690 (2022) - Sungkyu Kim, Tae-Seong Kim, Won Hee Lee:
Accelerating 3D Convolutional Neural Network with Channel Bottleneck Module for EEG-Based Emotion Recognition. Sensors 22(18): 6813 (2022) - 2021
- Edwin Valarezo Añazco, Patricio Rivera Lopez, Nahyeon Park, Jiheon Oh, Gahyeon Ryu, Mugahed A. Al-antari, Tae-Seong Kim:
Natural object manipulation using anthropomorphic robotic hand through deep reinforcement learning and deep grasping probability network. Appl. Intell. 51(2): 1041-1055 (2021) - Edwin Valarezo Añazco, Patricio Rivera Lopez, Tae-Seong Kim:
Three-dimensional shape reconstruction of objects from a single depth view using deep U-Net convolutional neural network with bottle-neck skip connections. IET Comput. Vis. 15(1): 24-35 (2021) - Patricio Rivera, Edwin Valarezo, Tae-Seong Kim:
An Integrated ARMA-Based Deep Autoencoder and GRU Classifier System for Enhanced Recognition of Daily Hand Activities. Int. J. Pattern Recognit. Artif. Intell. 35(6): 2152006:1-2152006:19 (2021) - Jongwan Kim, Taeseong Kim:
Improving Computational Thinking Comprehension through Visualized Sorting App Development. J. Multim. Inf. Syst. 8(3): 191-196 (2021) - Yohan Jun, Hyungseob Shin, Taejoon Eo, Taeseong Kim, Dosik Hwang:
Deep model-based magnetic resonance parameter mapping network (DOPAMINE) for fast T1 mapping using variable flip angle method. Medical Image Anal. 70: 102017 (2021) - Edwin Valarezo Añazco, Seungju Han, Kangil Kim, Patricio Rivera Lopez, Tae-Seong Kim, Sangmin Lee:
Hand Gesture Recognition Using Single Patchable Six-Axis Inertial Measurement Unit via Recurrent Neural Networks. Sensors 21(4): 1404 (2021) - Patricio Rivera, Edwin Valarezo Añazco, Tae-Seong Kim:
Object Manipulation with an Anthropomorphic Robotic Hand via Deep Reinforcement Learning with a Synergy Space of Natural Hand Poses. Sensors 21(16): 5301 (2021) - Patricio Rivera, Jiheon Oh, Edwin Valarezo, Gahyeon Ryu, Hwanseok Jung, Jin Hyunk Lee, Jin Gyun Jeong, Tae-Seong Kim:
Reward Shaping to Learn Natural Object Manipulation With an Anthropomorphic Robotic Hand and Hand Pose Priors via On-Policy Reinforcement Learning. ICTC 2021: 167-171 - Fahad Ahmed Satti, Musarrat Hussain, Jamil Hussain, Tae-Seong Kim, Sungyoung Lee, TaeChoong Chung:
User Stress Modeling through Galvanic Skin Response. IMCOM 2021: 1-6 - Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll:
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI 2021: 25-34 - 2020
- Mugahed A. Al-antari, Seung-Moo Han, Tae-Seong Kim:
Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms. Comput. Methods Programs Biomed. 196: 105584 (2020) - Mohammed A. Al-masni, Dong-Hyun Kim, Tae-Seong Kim:
Multiple skin lesions diagnostics via integrated deep convolutional networks for segmentation and classification. Comput. Methods Programs Biomed. 190: 105351 (2020) - Taejoon Eo, Hyungseob Shin, Yohan Jun, Taeseong Kim, Dosik Hwang:
Accelerating Cartesian MRI by domain-transform manifold learning in phase-encoding direction. Medical Image Anal. 63: 101689 (2020) - Luke Rieman, Erdogan Guk, Taeseong Kim, Chankyu Son, Jung-Sik Kim:
Development of a Novel Multi-Channel Thermocouple Array Sensor for In-Situ Monitoring of Ice Accretion. Sensors 20(8): 2165 (2020) - 2019
- Patricio Rivera, Edwin Valarezo Añazco, Mun-Taek Choi, Tae-Seong Kim:
Trilateral convolutional neural network for 3D shape reconstruction of objects from a single depth view. IET Image Process. 13(13): 2457-2466 (2019) - Sang Jae Cho, Bo Seong Kim, Tae-Seon Kim, Seung-Hyun Kong:
Enhancing GNSS Performance and Detection of Road Crossing in Urban Area Using Deep Learning. ITSC 2019: 2115-2120 - 2018
- Mohammed A. Al-masni, Mugahed A. Al-antari, Mun-Taek Choi, Seung-Moo Han, Tae-Seong Kim:
Skin lesion segmentation in dermoscopy images via deep full resolution convolutional networks. Comput. Methods Programs Biomed. 162: 221-231 (2018) - Mohammed A. Al-masni, Mugahed A. Al-antari, Jeong-min Park, Geon Gi, Tae-Yeon Kim, Patricio Rivera, Edwin Valarezo, Mun-Taek Choi, Seung-Moo Han, Tae-Seong Kim:
Simultaneous Detection and Classification of Breast Masses in Digital Mammograms via a Deep Learning YOLO-based CAD System. Comput. Methods Programs Biomed. 157 (2018) - Mugahed A. Al-antari, Mohammed A. Al-masni, Mun-Taek Choi, Seung-Moo Han, Tae-Seong Kim:
A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification. Int. J. Medical Informatics 117: 44-54 (2018)
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