204 citations · 438 across the 21 of their papers we have counts for
21 papers
RankingMatch: Delving into Semi-Supervised Learning with Consistency Regularization and Ranking Loss
Trung Q. Tran, Mingu Kang, Daeyoung Kim
Semi-supervised learning (SSL) has played an important role in leveraging unlabeled data when labeled data is limited. One of the most successful SSL approaches is based on consist…
The effectiveness of feature attribution methods and its correlation with automatic evaluation scores
Giang Nguyen, Daeyoung Kim, Anh Nguyen
Explaining the decisions of an Artificial Intelligence (AI) model is increasingly critical in many real-world, high-stake applications. Hundreds of papers have either proposed new…
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
Previous works on neural text-to-speech (TTS) have been addressed on limited speed in training and inference time, robustness for difficult synthesis conditions, expressiveness, an…
QuickBrowser: A Unified Model to Detect and Read Simple Object in Real-time
Thao Do, Daeyoung Kim
There are many real-life use cases such as barcode scanning or billboard reading where people need to detect objects and read the object contents. Commonly existing methods are fir…
CAP-GAN: Towards Adversarial Robustness with Cycle-consistent Attentional Purification
Mingu Kang, Trung Quang Tran, Seungju Cho +1
Adversarial attack is aimed at fooling the target classifier with imperceptible perturbation. Adversarial examples, which are carefully crafted with a malicious purpose, can lead t…
ReRankMatch: Semi-Supervised Learning with Semantics-Oriented Similarity Representation
Trung Quang Tran, Mingu Kang, Daeyoung Kim
This paper proposes integrating semantics-oriented similarity representation into RankingMatch, a recently proposed semi-supervised learning method. Our method, dubbed ReRankMatch,…
Adversarial Optimal Transport Through The Convolution Of Kernels With Evolving Measures
Daeyoung Kim, Esteban G. Tabak
A novel algorithm is proposed to solve the sample-based optimal transport problem. An adversarial formulation of the push-forward condition uses a test function built as a convolut…
Explaining How Deep Neural Networks Forget by Deep Visualization
Giang Nguyen, Shuan Chen, Tae Joon Jun +1
Explaining the behaviors of deep neural networks, usually considered as black boxes, is critical especially when they are now being adopted over diverse aspects of human life. Taki…
Simple Multi-Resolution Representation Learning for Human Pose Estimation
Trung Q. Tran, Giang V. Nguyen, Daeyoung Kim
Human pose estimation - the process of recognizing human keypoints in a given image - is one of the most important tasks in computer vision and has a wide range of applications inc…
Smart Inference for Multidigit Convolutional Neural Network based Barcode Decoding
Thao Do, Yalew Tolcha, Tae Joon Jun +1
Barcodes are ubiquitous and have been used in most of critical daily activities for decades. However, most of traditional decoders require well-founded barcode under a relatively s…
Applying Tensor Decomposition to image for Robustness against Adversarial Attack
Seungju Cho, Tae Joon Jun, Mingu Kang +1
Nowadays the deep learning technology is growing faster and shows dramatic performance in computer vision areas. However, it turns out a deep learning based model is highly vulnera…
Unbalanced GANs: Pre-training the Generator of Generative Adversarial Network using Variational Autoencoder
Hyungrok Ham, Tae Joon Jun, Daeyoung Kim
We propose Unbalanced GANs, which pre-trains the generator of the generative adversarial network (GAN) using variational autoencoder (VAE). We guarantee the stable training of the…
Dissecting Catastrophic Forgetting in Continual Learning by Deep Visualization
Giang Nguyen, Shuan Chen, Thao Do +3
Interpreting the behaviors of Deep Neural Networks (usually considered as a black box) is critical especially when they are now being widely adopted over diverse aspects of human l…
ContCap: A scalable framework for continual image captioning
Giang Nguyen, Tae Joon Jun, Trung Tran +2
While advanced image captioning systems are increasingly describing images coherently and exactly, recent progress in continual learning allows deep learning models to avoid catast…
DAPAS : Denoising Autoencoder to Prevent Adversarial attack in Semantic Segmentation
Seungju Cho, Tae Joon Jun, Byungsoo Oh +1
Nowadays, Deep learning techniques show dramatic performance on computer vision area, and they even outperform human. But it is also vulnerable to some small perturbation called an…
T-Net: Nested encoder-decoder architecture for the main vessel segmentation in coronary angiography
Tae Joon Jun, Jihoon Kweon, Young-Hak Kim +1
In this paper, we proposed T-Net containing a small encoder-decoder inside the encoder-decoder structure (EDiED). T-Net overcomes the limitation that U-Net can only have a single s…
Tournament Based Ranking CNN for the Cataract grading
Dohyeun Kim, Tae Joon Jun, Daeyoung Kim +1
Solving the classification problem, unbalanced number of dataset among the classes often causes performance degradation. Especially when some classes dominate the other classes wit…
2sRanking-CNN: A 2-stage ranking-CNN for diagnosis of glaucoma from fundus images using CAM-extracted ROI as an intermediate input
Tae Joon Jun, Dohyeun Kim, Hoang Minh Nguyen +2
Glaucoma is a disease in which the optic nerve is chronically damaged by the elevation of the intra-ocular pressure, resulting in visual field defect. Therefore, it is important to…
Automated diagnosis of pneumothorax using an ensemble of convolutional neural networks with multi-sized chest radiography images
Tae Joon Jun, Dohyeun Kim, Daeyoung Kim
Pneumothorax is a relatively common disease, but in some cases, it may be difficult to find with chest radiography. In this paper, we propose a novel method of detecting pneumothor…
Automated detection of vulnerable plaque in intravascular ultrasound images
Tae Joon Jun, Soo-Jin Kang, June-Goo Lee +6
Acute Coronary Syndrome (ACS) is a syndrome caused by a decrease in blood flow in the coronary arteries. The ACS is usually related to coronary thrombosis and is primarily caused b…
ECG arrhythmia classification using a 2-D convolutional neural network
Tae Joon Jun, Hoang Minh Nguyen, Daeyoun Kang +3
In this paper, we propose an effective electrocardiogram (ECG) arrhythmia classification method using a deep two-dimensional convolutional neural network (CNN) which recently shows…