Daeyoung Kim

发表

The effectiveness of feature attribution methods and its correlation with automatic evaluation scores

Anh M Nguyen, Giang Nguyen, Daeyoung Kim, 2021, NeurIPS.

Efficient deep learning of image denoising using patch complexity local divide and deep conquer

Youngbae Hwang, Daeyoung Kim, Inpyo Hong, 2019, Pattern Recognit..

TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes pdf

Tae Joon Jun, Youngsub Eom, Dohyeun Kim, 2019, Expert Syst. Appl..

STYLER: Style Factor Modeling with Rapidity and Robustness via Speech Decomposition for Expressive and Controllable Neural Text to Speech

Keon Lee, Kyumin Park, Daeyoung Kim, 2021, Interspeech.

CAP-GAN: Towards Adversarial Robustness with Cycle-consistent Attentional Purification

Mingu Kang, Daeyoung Kim, Trung Quang Tran, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation

Tae Joon Jun, Daeyoung Kim, Byungsoo Oh, 2019, 2020 International Joint Conference on Neural Networks (IJCNN).

GPU Enabled Serverless Computing Framework

Tae Joon Jun, Dohyeun Kim, Daeyoung Kim, 2018, 2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP).

Automated diagnosis of pneumothorax using an ensemble of convolutional neural networks with multi-sized chest radiography images pdf

Tae Joon Jun, Dohyeun Kim, Daeyoung Kim, 2018, ArXiv.

ECG arrhythmia classification using a 2-D convolutional neural network pdf

Daeyoung Kim, Tae Joon Jun, Dohyeun Kim, 2018, ArXiv.

T-Net: Nested encoder-decoder architecture for the main vessel segmentation in coronary angiography

Tae Joon Jun, Daeyoung Kim, Young-Hak Kim, 2020, Neural Networks.

T-Net: Nested encoder-decoder architecture for the main vessel segmentation in coronary angiography

Tae Joon Jun, Daeyoung Kim, Jihoon Kweon, 2020, Neural Networks.

Unbalanced GANs: Pre-training the Generator of Generative Adversarial Network using Variational Autoencoder pdf

Tae Joon Jun, Daeyoung Kim, Hyungrok Ham, 2020, ArXiv.

RankingMatch: Delving into Semi-Supervised Learning with Consistency Regularization and Ranking Loss pdf

Daeyoung Kim, Mingu Kang, Trung Q. Tran, 2021, ArXiv.

Explaining How Deep Neural Networks Forget by Deep Visualization

Giang Nguyen, Daeyoung Kim, T. Jun, 2020, ICPR Workshops.

Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization pdf

Tae Joon Jun, Daeyoung Kim, Ho-Jin Choi, 2020, ArXiv.

ContCap: A comprehensive framework for continual image captioning pdf

Tae Joon Jun, Daeyoung Kim, Giang Nguyen, 2019, ArXiv.

ContCap: A scalable framework for continual image captioning

T. Tran, Giang Nguyen, Daeyoung Kim, 2019, 1909.08745.

GPU based cloud system for high-performance arrhythmia detection with parallel k-NN algorithm

Tae Joon Jun, Daeyoung Kim, Hyun Ji Park, 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Premature Ventricular Contraction Beat Detection with Deep Neural Networks

Daeyoung Kim, Tae Joon Jun, Hoang Minh Nguyen, 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

Tournament Based Ranking CNN for the Cataract grading

Tae Joon Jun, Youngsub Eom, Dohyeun Kim, 2018, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Automated detection of vulnerable plaque in intravascular ultrasound images

Tae Joon Jun, Dohyeun Kim, June-Goo Lee, 2018, Medical & Biological Engineering & Computing.

Thin-Cap Fibroatheroma Detection with Deep Neural Networks

Tae Joon Jun, Dohyeun Kim, June-Goo Lee, 2017, ICONIP.

T-Net: Encoder-Decoder in Encoder-Decoder architecture for the main vessel segmentation in coronary angiography

Young-Hak Kim, Daeyoung Kim, T. Jun, 2019, ArXiv.

Quick Browser: A Unified Model to Detect and Read Simple Object in Real-time

Daeyoung Kim, T. Do, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).