Seong Tae Kim

Orcid: 0000-0002-2132-6021

Affiliations:
  • Kyung Hee University, South Korea
  • Technical University of Munich, Department of Informatics, Germany (former)
  • KAIST, Image and Video Systems Laboratory, Daejeon, South Korea (former)


According to our database1, Seong Tae Kim authored at least 66 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning.
Neural Networks, 2024

MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object Detection.
CoRR, 2024

Mask-Free Neuron Concept Annotation for Interpreting Neural Networks in Medical Domain.
CoRR, 2024

WWW: A Unified Framework for Explaining What, Where and Why of Neural Networks by Interpretation of Neuron Concepts.
CoRR, 2024

Do You Remember? Dense Video Captioning with Cross-Modal Memory Retrieval.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Exploiting recollection effects for memory-based video object segmentation.
Image Vis. Comput., December, 2023

A Hybrid Multimodal Emotion Recognition Framework for UX Evaluation Using Generalized Mixture Functions.
Sensors, 2023

One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era.
CoRR, 2023

Time Series Anomaly Detection Using Transformer-Based GAN With Two-Step Masking.
IEEE Access, 2023

Improved Abdominal Multi-Organ Segmentation via 3D Boundary-Constrained Deep Neural Networks.
IEEE Access, 2023

Interactive Segmentation for COVID-19 Infection Quantification on Longitudinal CT Scans.
IEEE Access, 2023

Toward Label-Efficient Neural Network Training: Diversity-Based Sampling in Semi-Supervised Active Learning.
IEEE Access, 2023

Towards Robust Audio-Based Vehicle Detection Via Importance-Aware Audio-Visual Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023

LINe: Out-of-Distribution Detection by Leveraging Important Neurons.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Robust Perturbation for Visual Explanation: Cross-Checking Mask Optimization to Avoid Class Distortion.
IEEE Trans. Image Process., 2022

Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models.
CoRR, 2022

Longitudinal Self-Supervision for COVID-19 Pathology Quantification.
CoRR, 2022

Exploiting Diversity of Unlabeled Data for Label-Efficient Semi-Supervised Active Learning.
Proceedings of the 26th International Conference on Pattern Recognition, 2022

2021
CUA Loss: Class Uncertainty-Aware Gradient Modulation for Robust Object Detection.
IEEE Trans. Circuits Syst. Video Technol., 2021

GLOWin: A Flow-based Invertible Generative Framework for Learning Disentangled Feature Representations in Medical Images.
CoRR, 2021

Longitudinal Brain MR Image Modeling Using Personalized Memory for Alzheimer's Disease.
IEEE Access, 2021

Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Longitudinal Quantitative Assessment of COVID-19 Infection Progression from Chest CTs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

OperA: Attention-Regularized Transformers for Surgical Phase Recognition.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Butterfly-Net: Spatial-Temporal Architecture For Medical Image Segmentation.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Neural Response Interpretation Through the Lens of Critical Pathways.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020
Lightweight and Effective Facial Landmark Detection using Adversarial Learning with Face Geometric Map Generative Network.
IEEE Trans. Circuits Syst. Video Technol., 2020

Force-Ultrasound Fusion: Bringing Spine Robotic-US to the Next "Level".
IEEE Robotics Autom. Lett., 2020

Multimodal facial biometrics recognition: Dual-stream convolutional neural networks with multi-feature fusion layers.
Image Vis. Comput., 2020

Self-Supervised Out-of-Distribution Detection in Brain CT Scans.
CoRR, 2020

Efficient Ensemble Model Generation for Uncertainty Estimation with Bayesian Approximation in Segmentation.
CoRR, 2020

Confident Coreset for Active Learning in Medical Image Analysis.
CoRR, 2020

TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Towards High-Performance Object Detection: Task-Specific Design Considering Classification and Localization Separation.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Spatio-Temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

2019
Attended Relation Feature Representation of Facial Dynamics for Facial Authentication.
IEEE Trans. Inf. Forensics Secur., 2019

Implementation of multimodal biometric recognition via multi-feature deep learning networks and feature fusion.
Multim. Tools Appl., 2019

Explaining Neural Networks via Perturbing Important Learned Features.
CoRR, 2019

Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis.
Proceedings of the Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support, 2019

Realistic Breast Mass Generation Through BIRADS Category.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Visual evidence for interpreting diagnostic decision of deep neural network in computer-aided diagnosis.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019

Probenet: Probing Deep Networks.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Building a Breast-Sentence Dataset: Its Usefulness for Computer-Aided Diagnosis.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

2018
Convolution with Logarithmic Filter Groups for Efficient Shallow CNN.
Proceedings of the MultiMedia Modeling - 24th International Conference, 2018

Teacher and Student Joint Learning for Compact Facial Landmark Detection Network.
Proceedings of the MultiMedia Modeling - 24th International Conference, 2018

ICADx: interpretable computer aided diagnosis of breast masses.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018

Feature2Mass: Visual Feature Processing in Latent Space for Realistic Labeled Mass Generation.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Facial Dynamics Interpreter Network: What Are the Important Relations Between Local Dynamics for Facial Trait Estimation?
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
Interpretable Facial Relational Network Using Relational Importance.
CoRR, 2017

Differential Generative Adversarial Networks: Synthesizing Non-linear Facial Variations with Limited Number of Training Data.
CoRR, 2017

EvaluationNet: Can Human Skill be Evaluated by Deep Networks?
CoRR, 2017

Adaptive attention fusion network for visual question answering.
Proceedings of the 2017 IEEE International Conference on Multimedia and Expo, 2017

Multi-Scale Facial Scanning via Spatial Lstm for Latent Facial Feature Representation.
Proceedings of the International Conference of the Biometrics Special Interest Group, 2017

2016
Spatio-temporal representation for face authentication by using multi-task learning with human attributes.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

A deep facial landmarks detection with facial contour and facial components constraint.
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

Latent feature representation with 3-D multi-view deep convolutional neural network for bilateral analysis in digital breast tomosynthesis.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

Facial dynamic modelling using long short-term memory network: Analysis and application to face authentication.
Proceedings of the 8th IEEE International Conference on Biometrics Theory, 2016

2015
Feature extraction from inter-view similarity of DBT projection views.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

Combination of conspicuity improved synthetic mammograms and digital breast tomosynthesis: a promising approach for mass detection.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015

Region matching based on local structure information in ipsilateral digital breast tomosynthesis views.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Feature extraction from bilateral dissimilarity in digital breast tomosynthesis reconstructed volume.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

2014
Generation of conspicuity-improved synthetic image from digital breast tomosynthesis.
Proceedings of the 19th International Conference on Digital Signal Processing, 2014

Mass detection based on pooled mass probability map of 3D reconstructed slices in digital breast tomosynthesis.
Proceedings of IEEE-EMBS International Conference on Biomedical and Health Informatics, 2014


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