Search Results for author: Seong-Whan Lee

Found 46 papers, 8 papers with code

Precise Aerial Image Matching based on Deep Homography Estimation

no code implementations19 Jul 2021 Myeong-Seok Oh, Yong-Ju Lee, Seong-Whan Lee

In this paper, we propose a deep homography alignment network to precisely match two aerial images by progressively estimating the various transformation parameters.

Homography Estimation Image Registration

Joint Dermatological Lesion Classification and Confidence Modeling with Uncertainty Estimation

no code implementations19 Jul 2021 Gun-Hee Lee, Han-Bin Ko, Seong-Whan Lee

Deep learning has played a major role in the interpretation of dermoscopic images for detecting skin defects and abnormalities.

Lesion Classification

Improving Interpretability of Deep Neural Networks in Medical Diagnosis by Investigating the Individual Units

no code implementations19 Jul 2021 Woo-Jeoung Nam, Seong-Whan Lee

As an intuitive assessment metric for explanations, we report the performance of intersection of Union between visual explanation and bounding box of lesions.

Medical Diagnosis

DAL: Feature Learning from Overt Speech to Decode Imagined Speech-based EEG Signals with Convolutional Autoencoder

no code implementations15 Jul 2021 Dae-Hyeok Lee, Sung-Jin Kim, Seong-Whan Lee

In addition, when comparing the performance between w/o and w/ EEG features of overt speech, there was a performance improvement of 7. 42% when including EEG features of overt speech.


Motor Imagery Classification based on CNN-GRU Network with Spatio-Temporal Feature Representation

no code implementations15 Jul 2021 Ji-Seon Bang, Seong-Whan Lee

In the classification model, CNN is responsible for spatial feature extraction and GRU is responsible for temporal feature extraction.


Detection of Abnormal Behavior with Self-Supervised Gaze Estimation

no code implementations14 Jul 2021 Suneung-Kim, Seong-Whan Lee

In this paper, we present a single video conferencing solution using gaze estimation in preparation for these problems.

Anomaly Detection Gaze Estimation

Towards Natural Brain-Machine Interaction using Endogenous Potentials based on Deep Neural Networks

no code implementations25 Jun 2021 Hyung-Ju Ahn, Dae-Hyeok Lee, Ji-Hoon Jeong, Seong-Whan Lee

Moreover, our proposed TINN showed the highest accuracy of 0. 93 compared to the previous methods for classifying three different types of mental imagery tasks (MI, VI, and SI).


Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks

no code implementations8 Jun 2021 Dae-Hyeok Lee, Dong-Kyun Han, Sung-Jin Kim, Ji-Hoon Jeong, Seong-Whan Lee

Communication between humans and a drone using electroencephalogram (EEG) signals is one of the most challenging issues in the BCI domain.


Reinforce-Aligner: Reinforcement Alignment Search for Robust End-to-End Text-to-Speech

no code implementations5 Jun 2021 Hyunseung Chung, Sang-Hoon Lee, Seong-Whan Lee

Experimental results also show the superiority of our proposed model compared to other state-of-the-art TTS models with internal and external aligners.

Fre-GAN: Adversarial Frequency-consistent Audio Synthesis

1 code implementation4 Jun 2021 Ji-Hoon Kim, Sang-Hoon Lee, Ji-Hyun Lee, Seong-Whan Lee

Although recent works on neural vocoder have improved the quality of synthesized audio, there still exists a gap between generated and ground-truth audio in frequency space.

ACNet: Mask-Aware Attention with Dynamic Context Enhancement for Robust Acne Detection

no code implementations31 May 2021 Kyungseo Min, Gun-Hee Lee, Seong-Whan Lee

To address these problems, we propose an acne detection network which consists of three components, specifically: Composite Feature Refinement, Dynamic Context Enhancement, and Mask-Aware Multi-Attention.

FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface

1 code implementation17 Mar 2021 Ravikiran Mane, Effie Chew, Karen Chua, Kai Keng Ang, Neethu Robinson, A. P. Vinod, Seong-Whan Lee, Cuntai Guan

With this design, we compare FBCNet with state-of-the-art (SOTA) BCI algorithm on four MI datasets: The BCI competition IV dataset 2a (BCIC-IV-2a), the OpenBMI dataset, and two large datasets from chronic stroke patients.

EEG General Classification

Decoding Event-related Potential from Ear-EEG Signals based on Ensemble Convolutional Neural Networks in Ambulatory Environment

no code implementations3 Mar 2021 Young-Eun Lee, Seong-Whan Lee

Recently, practical brain-computer interface is actively carried out, especially, in an ambulatory environment.


Weakly Supervised Thoracic Disease Localization via Disease Masks

no code implementations25 Jan 2021 Hyun-Woo Kim, Hong-Gyu Jung, Seong-Whan Lee

To enable a deep learning-based system to be used in the medical domain as a computer-aided diagnosis system, it is essential to not only classify diseases but also present the locations of the diseases.

Visual Question Answering based on Local-Scene-Aware Referring Expression Generation

no code implementations22 Jan 2021 Jung-Jun Kim, Dong-Gyu Lee, Jialin Wu, Hong-Gyu Jung, Seong-Whan Lee

We quantitatively and qualitatively evaluated the proposed method on the VQA v2 dataset and compared it with state-of-the-art methods in terms of answer prediction.

Question Answering Visual Question Answering

Human Interaction Recognition Framework based on Interacting Body Part Attention

no code implementations22 Jan 2021 Dong-Gyu Lee, Seong-Whan Lee

In this paper, we propose a novel framework that simultaneously considers both implicit and explicit representations of human interactions by fusing information of local image where the interaction actively occurred, primitive motion with the posture of individual subject's body parts, and the co-occurrence of overall appearance change.

Activity Recognition Activity Recognition In Videos +1

Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations

no code implementations7 Dec 2020 Woo-Jeoung Nam, Jaesik Choi, Seong-Whan Lee

As a result, it is possible to assign the bi-polar relevance scores of the target (positive) and hostile (negative) attributions while maintaining each attribution aligned with the importance.

Rotation Invariant Aerial Image Retrieval with Group Convolutional Metric Learning

no code implementations19 Oct 2020 Hyunseung Chung, Woo-Jeoung Nam, Seong-Whan Lee

In this work, we introduce a novel method for retrieving aerial images by merging group convolution with attention mechanism and metric learning, resulting in robustness to rotational variations.

Image Retrieval Metric Learning

Online Multi-Object Tracking and Segmentation with GMPHD Filter and Mask-based Affinity Fusion

1 code implementation31 Aug 2020 Young-min Song, Young-chul Yoon, Kwangjin Yoon, Moongu Jeon, Seong-Whan Lee, Witold Pedrycz

One affinity, for position and motion, is computed by using the GMPHD filter, and the other affinity, for appearance is computed by using the responses from a single object tracker such as a kernalized correlation filter.

Instance Segmentation Multi-Object Tracking +3

Decoding Visual Recognition of Objects from EEG Signals based on Attention-Driven Convolutional Neural Network

no code implementations28 Aug 2020 Jenifer Kalafatovich, Minji Lee, Seong-Whan Lee

Our findings showed that EEG signals are possible to differentiate when subjects are presented with visual stimulus of different semantic categories and at an exemplar-level with a high classification accuracy; this demonstrates its viability to be applied it in a real-world BMI.

EEG General Classification

Classification of Imagined Speech Using Siamese Neural Network

no code implementations28 Aug 2020 Dong-Yeon Lee, Minji Lee, Seong-Whan Lee

The proposed framework would help to increase the classification performance of imagined speech for a small amount of data and implement an intuitive communication system.

EEG General Classification

Few-Shot Object Detection via Knowledge Transfer

no code implementations28 Aug 2020 Geonuk Kim, Hong-Gyu Jung, Seong-Whan Lee

If there are only a few training data and annotations, the object detectors easily overfit and fail to generalize.

Few-Shot Object Detection Transfer Learning

Counterfactual Explanation Based on Gradual Construction for Deep Networks

no code implementations5 Aug 2020 Sin-Han Kang, Hong-Gyu Jung, Dong-Ok Won, Seong-Whan Lee

The masking step aims to select an important feature from the input data to be classified as a target class.

Counterfactual Explanation

Reconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface

no code implementations18 May 2020 Young-Eun Lee, Minji Lee, Seong-Whan Lee

As a result, the reconstructed signals had important components such as N200 and P300 similar to ERP during standing.


Decoding of Intuitive Visual Motion Imagery Using Convolutional Neural Network under 3D-BCI Training Environment

no code implementations15 May 2020 Byoung-Hee Kwon, Ji-Hoon Jeong, Jeong-Hyun Cho, Seong-Whan Lee

As a result, the averaged classification performance of the proposed architecture for 4 classes from 16 channels was 67. 50 % across all subjects.

General Classification Platform

Assessment of Unconsciousness for Memory Consolidation Using EEG Signals

no code implementations15 May 2020 Gi-Hwan Shin, Minji Lee, Seong-Whan Lee

Seven participants performed two memory tasks (word-pairs and visuo-spatial) before and after the nap to assess the memory consolidation during unconsciousness.


Prediction of Memory Retrieval Performance Using Ear-EEG Signals

no code implementations4 May 2020 Jenifer Kalafatovich, Minji Lee, Seong-Whan Lee

These results showed that it is possible to predict performance of a memory task using ear-EEG signals and it could be used for predicting memory retrieval in a practical brain-computer interface.


End-to-End Automatic Sleep Stage Classification Using Spectral-Temporal Sleep Features

no code implementations4 May 2020 Hyeong-Jin Kim, Minji Lee, Seong-Whan Lee

For five sleep stage classification, the classification performance 85. 6% and 91. 1% using the raw input data and the proposed input, respectively.

Automatic Sleep Stage Classification General Classification

Few-Shot Learning with Geometric Constraints

no code implementations20 Mar 2020 Hong-Gyu Jung, Seong-Whan Lee

We assume a network trained for base categories with a large number of training examples, and we aim to add novel categories to it that have only a few, e. g., one or five, training examples.

Few-Shot Learning

A Novel Online Action Detection Framework from Untrimmed Video Streams

no code implementations17 Mar 2020 Da-Hye Yoon, Nam-Gyu Cho, Seong-Whan Lee

Online temporal action localization from an untrimmed video stream is a challenging problem in computer vision.

Action Detection Temporal Action Localization

Three-Stream Fusion Network for First-Person Interaction Recognition

no code implementations19 Feb 2020 Ye-Ji Kim, Dong-Gyu Lee, Seong-Whan Lee

First-person interaction recognition is a challenging task because of unstable video conditions resulting from the camera wearer's movement.

Activity Recognition Human Interaction Recognition

A Two-Stream Symmetric Network with Bidirectional Ensemble for Aerial Image Matching

2 code implementations4 Feb 2020 Jae-Hyun Park, Woo-Jeoung Nam, Seong-Whan Lee

As a result, the training process of the deep network is regularized and the network becomes robust for the variance of aerial images.

Towards Brain-Computer Interfaces for Drone Swarm Control

no code implementations3 Feb 2020 Ji-Hoon Jeong, Dae-Hyeok Lee, Hyung-Ju Ahn, Seong-Whan Lee

Hence, we could confirm the feasibility of the drone swarm control system based on EEG signals for performing high-level tasks.

EEG General Classification

Mel-spectrogram augmentation for sequence to sequence voice conversion

2 code implementations6 Jan 2020 Yeongtae Hwang, Hyemin Cho, Hongsun Yang, Dong-Ok Won, Insoo Oh, Seong-Whan Lee

In addition, we proposed new policies (i. e., frequency warping, loudness and time length control) for more data variations.

Voice Conversion

Network of Evolvable Neural Units: Evolving to Learn at a Synaptic Level

no code implementations16 Dec 2019 Paul Bertens, Seong-Whan Lee

Here a model is proposed that bridges Neuroscience, Machine Learning and Evolutionary Algorithms to evolve individual soma and synaptic compartment models of neurons in a scalable manner.

Interpreting Undesirable Pixels for Image Classification on Black-Box Models

no code implementations27 Sep 2019 Sin-Han Kang, Hong-Gyu Jung, Seong-Whan Lee

To tackle this issue, in this paper, we propose an explanation method that visualizes undesirable regions to classify an image as a target class.

General Classification Image Classification

Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks

1 code implementation1 Apr 2019 Woo-Jeoung Nam, Shir Gur, Jaesik Choi, Lior Wolf, Seong-Whan Lee

As Deep Neural Networks (DNNs) have demonstrated superhuman performance in a variety of fields, there is an increasing interest in understanding the complex internal mechanisms of DNNs.

Deep Reinforcement Learning in Continuous Action Spaces: a Case Study in the Game of Simulated Curling

1 code implementation ICML 2018 Kyowoon Lee, Sol-A Kim, Jaesik Choi, Seong-Whan Lee

Many real-world applications of reinforcement learning require an agent to select optimal actions from continuous spaces.

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