Seong Tae Kim

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 64

Top Topics

Computer Aided Diagnosis

Top Venues

Medical Imaging: Computer-Aided Diagnosis

Publications

Hyeon Bae Kim, Yong Hyun Ahn, Seong Tae Kim
Mask-Free Neuron Concept Annotation for Interpreting Neural Networks in Medical Domain. CoRR (2024)
Yong Hyun Ahn, Hyeon Bae Kim, Seong Tae Kim
WWW: A Unified Framework for Explaining What, Where and Why of Neural Networks by Interpretation of Neuron Concepts. CoRR (2024)
Chu Myaet Thwal, Minh N. H. Nguyen, Ye Lin Tun, Seong Tae Kim, My T. Thai, Choong Seon Hong
OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning. CoRR (2024)
Youngmin Oh, Hyung-Il Kim, Seong Tae Kim, Jung Uk Kim
MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object Detection. CoRR (2024)
Chu Myaet Thwal, Minh N. H. Nguyen, Ye Lin Tun, Seong Tae Kim, My T. Thai, Choong Seon Hong
OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning. Neural Networks 170 (2024)
Michelle Xiao-Lin Foo, Seong Tae Kim, Magdalini Paschali, Leili Goli, Egon Burian, Marcus R. Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler
Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT Scans. IEEE Access 11 (2023)
Ah-Hyung Shin, Seong Tae Kim, Gyeong-Moon Park
Time Series Anomaly Detection Using Transformer-Based GAN With Two-Step Masking. IEEE Access 11 (2023)
Muhammad Asif Razzaq, Jamil Hussain, Jaehun Bang, Cam-Hao Hua, Fahad Ahmed Satti, Ubaid Ur Rehman, Hafiz Syed Muhammad Bilal, Seong Tae Kim, Sungyoung Lee
A Hybrid Multimodal Emotion Recognition Framework for UX Evaluation Using Generalized Mixture Functions. Sensors 23 (9) (2023)
Felix Buchert, Nassir Navab, Seong Tae Kim
Toward Label-Efficient Neural Network Training: Diversity-Based Sampling in Semi-Supervised Active Learning. IEEE Access 11 (2023)
Samra Irshad, Douglas P. S. Gomes, Seong Tae Kim
Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks. IEEE Access 11 (2023)
Yong Hyun Ahn, Gyeong-Moon Park, Seong Tae Kim
LINe: Out-of-Distribution Detection by Leveraging Important Neurons. CVPR (2023)
Junho Kim, Seongyeop Kim, Seong Tae Kim, Yong Man Ro
Robust Perturbation for Visual Explanation: Cross-Checking Mask Optimization to Avoid Class Distortion. IEEE Trans. Image Process. 31 (2022)
Felix Buchert, Nassir Navab, Seong Tae Kim
Exploiting Diversity of Unlabeled Data for Label-Efficient Semi-Supervised Active Learning. ICPR (2022)
Tobias Czempiel, Coco Rogers, Matthias Keicher, Magdalini Paschali, Rickmer Braren, Egon Burian, Marcus R. Makowski, Nassir Navab, Thomas Wendler, Seong Tae Kim
Longitudinal Self-Supervision for COVID-19 Pathology Quantification. CoRR (2022)
Felix Buchert, Nassir Navab, Seong Tae Kim
Exploiting Diversity of Unlabeled Data for Label-Efficient Semi-Supervised Active Learning. CoRR (2022)
Ashkan Khakzar, Yawei Li, Yang Zhang, Mirac Sanisoglu, Seong Tae Kim, Mina Rezaei, Bernd Bischl, Nassir Navab
Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models. CoRR (2022)
Yang Zhang, Ashkan Khakzar, Yawei Li, Azade Farshad, Seong Tae Kim, Nassir Navab
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information. NeurIPS (2021)
Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Christian Rupprecht, Seong Tae Kim, Nassir Navab
Neural Response Interpretation Through the Lens of Critical Pathways. CVPR (2021)
Ashkan Khakzar, Yang Zhang, Wejdene Mansour, Yuezhi Cai, Yawei Li, Yucheng Zhang, Seong Tae Kim, Nassir Navab
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features. CoRR (2021)
Seong Tae Kim, Umut Küçükaslan, Nassir Navab
Longitudinal Brain MR Image Modeling Using Personalized Memory for Alzheimer's Disease. IEEE Access 9 (2021)
Michelle Xiao-Lin Foo, Seong Tae Kim, Magdalini Paschali, Leili Goli, Egon Burian, Marcus R. Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler
Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT scans. CoRR (2021)
Seong Tae Kim, Leili Goli, Magdalini Paschali, Ashkan Khakzar, Matthias Keicher, Tobias Czempiel, Egon Burian, Rickmer Braren, Nassir Navab, Thomas Wendler
Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs. MICCAI (7) (2021)
Ashkan Khakzar, Yang Zhang, Wejdene Mansour, Yuezhi Cai, Yawei Li, Yucheng Zhang, Seong Tae Kim, Nassir Navab
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features. MICCAI (3) (2021)
Tobias Czempiel, Magdalini Paschali, Daniel Ostler, Seong Tae Kim, Benjamin Busam, Nassir Navab
OperA: Attention-Regularized Transformers for Surgical Phase Recognition. MICCAI (4) (2021)
Ashkan Khakzar, Sabrina Musatian, Jonas Buchberger, Icxel Valeriano Quiroz, Nikolaus Pinger, Soroosh Baselizadeh, Seong Tae Kim, Nassir Navab
Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models. MICCAI (3) (2021)
Yang Zhang, Ashkan Khakzar, Yawei Li, Azade Farshad, Seong Tae Kim, Nassir Navab
Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information. CoRR (2021)
Ashkan Khakzar, Sabrina Musatian, Jonas Buchberger, Icxel Valeriano Quiroz, Nikolaus Pinger, Soroosh Baselizadeh, Seong Tae Kim, Nassir Navab
Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models. CoRR (2021)
Tetiana Klymenko, Seong Tae Kim, Kirsten Lauber, Christopher Kurz, Guillaume Landry, Nassir Navab, Shadi Albarqouni
Butterfly-Net: Spatial-Temporal Architecture For Medical Image Segmentation. ISBI (2021)
Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Christian Rupprecht, Seong Tae Kim, Nassir Navab
Neural Response Interpretation through the Lens of Critical Pathways. CoRR (2021)
Abinav Ravi Venkatakrishnan, Seong Tae Kim, Rami Eisawy, Franz Pfister, Nassir Navab
Self-Supervised Out-of-Distribution Detection in Brain CT Scans. CoRR (2020)
Seong Tae Kim, Farrukh Mushtaq, Nassir Navab
Confident Coreset for Active Learning in Medical Image Analysis. CoRR (2020)
Hong Joo Lee, Seong Tae Kim, Hakmin Lee, Yong Man Ro
Lightweight and Effective Facial Landmark Detection using Adversarial Learning with Face Geometric Map Generative Network. IEEE Trans. Circuits Syst. Video Technol. 30 (3) (2020)
Maria Tirindelli, Maria Victorova, Javier Esteban, Seong Tae Kim, David Navarro-Alarcon, Yong-Ping Zheng, Nassir Navab
Force-Ultrasound Fusion: Bringing Spine Robotic-US to the Next "Level". CoRR (2020)
Maria Tirindelli, Maria Victorova, Javier Esteban, Seong Tae Kim, David Navarro-Alarcon, Yong-Ping Zheng, Nassir Navab
Force-Ultrasound Fusion: Bringing Spine Robotic-US to the Next "Level". IEEE Robotics Autom. Lett. 5 (4) (2020)
Hakmin Lee, Hong Joo Lee, Seong Tae Kim, Yong Man Ro
Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack. BMVC (2020)
Tobias Czempiel, Magdalini Paschali, Matthias Keicher, Walter Simson, Hubertus Feussner, Seong Tae Kim, Nassir Navab
TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks. CoRR (2020)
Jung Uk Kim, Seong Tae Kim, Eun Sung Kim, Sang-Keun Moon, Yong Man Ro
Towards High-Performance Object Detection: Task-Specific Design Considering Classification and Localization Separation. ICASSP (2020)
Tobias Czempiel, Magdalini Paschali, Matthias Keicher, Walter Simson, Hubertus Feussner, Seong Tae Kim, Nassir Navab
TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks. MICCAI (3) (2020)
Hong Joo Lee, Seong Tae Kim, Hakmin Lee, Nassir Navab, Yong Man Ro
Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation. CoRR (2020)
Stefan Denner, Ashkan Khakzar, Moiz Sajid, Mahdi Saleh, Ziga Spiclin, Seong Tae Kim, Nassir Navab
Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation. CoRR (2020)
Leslie Ching Ow Tiong, Seong Tae Kim, Yong Man Ro
Multimodal facial biometrics recognition: Dual-stream convolutional neural networks with multi-feature fusion layers. Image Vis. Comput. 102 (2020)
Hakmin Lee, Hong Joo Lee, Seong Tae Kim, Yong Man Ro
Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack. CoRR (2020)
Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Seong Tae Kim, Nassir Navab
Explaining Neural Networks via Perturbing Important Learned Features. CoRR (2019)
Seong Tae Kim, Jae-Hyeok Lee, Yong Man Ro
Visual evidence for interpreting diagnostic decision of deep neural network in computer-aided diagnosis. Medical Imaging: Computer-Aided Diagnosis (2019)
Hyebin Lee, Seong Tae Kim, Yong Man Ro
Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis. iMIMIC/ML-CDS@MICCAI (2019)
Hakmin Lee, Seong Tae Kim, Jae-Hyeok Lee, Yong Man Ro
Realistic Breast Mass Generation Through BIRADS Category. MICCAI (6) (2019)
Leslie Ching Ow Tiong, Seong Tae Kim, Yong Man Ro
Implementation of multimodal biometric recognition via multi-feature deep learning networks and feature fusion. Multim. Tools Appl. 78 (16) (2019)
Hyebin Lee, Seong Tae Kim, Yong Man Ro
Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis. CoRR (2019)
Jae-Hyeok Lee, Seong Tae Kim, Yong Man Ro
Probenet: Probing Deep Networks. ICIP (2019)
Seong Tae Kim, Yong Man Ro
Attended Relation Feature Representation of Facial Dynamics for Facial Authentication. IEEE Trans. Inf. Forensics Secur. 14 (7) (2019)
Hyebin Lee, Seong Tae Kim, Yong Man Ro
Building a Breast-Sentence Dataset: Its Usefulness for Computer-Aided Diagnosis. ICCV Workshops (2019)
Tae Kwan Lee, Wissam J. Baddar, Seong Tae Kim, Yong Man Ro
Convolution with Logarithmic Filter Groups for Efficient Shallow CNN. MMM (1) (2018)
Seong Tae Kim, Yong Man Ro
Facial Dynamics Interpreter Network: What Are the Important Relations Between Local Dynamics for Facial Trait Estimation? ECCV (12) (2018)
Seong Tae Kim, Hakmin Lee, Hak Gu Kim, Yong Man Ro
ICADx: interpretable computer aided diagnosis of breast masses. Medical Imaging: Computer-Aided Diagnosis (2018)
Jae-Hyeok Lee, Seong Tae Kim, Hakmin Lee, Yong Man Ro
Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation. CoRR (2018)
Seong Tae Kim, Hakmin Lee, Hak Gu Kim, Yong Man Ro
ICADx: Interpretable computer aided diagnosis of breast masses. CoRR (2018)
Hong Joo Lee, Wissam J. Baddar, Hak Gu Kim, Seong Tae Kim, Yong Man Ro
Teacher and Student Joint Learning for Compact Facial Landmark Detection Network. MMM (1) (2018)
Jae-Hyeok Lee, Seong Tae Kim, Hakmin Lee, Yong Man Ro
Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation. ECCV Workshops (6) (2018)
Seong Tae Kim, Yong Man Ro
Interpretable Facial Relational Network Using Relational Importance. CoRR (2017)
Geonmo Gu, Seong Tae Kim, Ki Hyun Kim, Wissam J. Baddar, Yong Man Ro
Differential Generative Adversarial Networks: Synthesizing Non-linear Facial Variations with Limited Number of Training Data. CoRR (2017)
Seong Tae Kim, Yeoreum Choi, Yong Man Ro
Multi-Scale Facial Scanning via Spatial Lstm for Latent Facial Feature Representation. BIOSIG (2017)
Seong Tae Kim, Yong Man Ro
EvaluationNet: Can Human Skill be Evaluated by Deep Networks? CoRR (2017)
Tae Kwan Lee, Wissam J. Baddar, Seong Tae Kim, Yong Man Ro
Convolution with Logarithmic Filter Groups for Efficient Shallow CNN. CoRR (2017)
Geonmo Gu, Seong Tae Kim, Yong Man Ro
Adaptive attention fusion network for visual question answering. ICME (2017)
Seong Tae Kim, Dae Hoe Kim, Yong Man Ro
Combination of conspicuity improved synthetic mammograms and digital breast tomosynthesis: a promising approach for mass detection. Medical Imaging: Computer-Aided Diagnosis (2015)
Dae Hoe Kim, Seong Tae Kim, Yong Man Ro
Feature extraction from inter-view similarity of DBT projection views. Medical Imaging: Computer-Aided Diagnosis (2015)