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2020 – today
- 2024
[j12]Jiho Bae
, Seok-Jun Buu, Suwon Lee:
Anchor-Net: Distance-Based Self-Supervised Learning Model for Facial Beauty Prediction. IEEE Access 12: 61375-61387 (2024)- [j11]Robin Inho Kee, Dahyun Nam, Seok-Jun Bu, Sung-Bae Cho:
Disentangled Prototypical Convolutional Network for Few-Shot Learning in In-Vehicle Noise Classification. IEEE Access 12: 66801-66808 (2024) - [j10]Junha Kang, Seok-Jun Bu:
Graph Anomaly Detection With Disentangled Prototypical Autoencoder for Phishing Scam Detection in Cryptocurrency Transactions. IEEE Access 12: 91075-91088 (2024) - [j9]Hyeon-Ju Lee, Seok-Jun Buu:
Deep Generative Replay With Denoising Diffusion Probabilistic Models for Continual Learning in Audio Classification. IEEE Access 12: 134714-134727 (2024) - [j8]Seok-Hun Choi, Seok-Jun Buu:
Disentangled Prototype-Guided Dynamic Memory Replay for Continual Learning in Acoustic Signal Classification. IEEE Access 12: 153796-153808 (2024) - 2023
- [j7]Hyung-Jun Moon, Seok-Jun Bu, Sung-Bae Cho:
A graph convolution network with subgraph embedding for mutagenic prediction in aromatic hydrocarbons. Neurocomputing 530: 60-68 (2023) - [j6]Seok-Jun Bu, Sung-Bae Cho:
Malware classification with disentangled representation learning of evolutionary triplet network. Neurocomputing 552: 126534 (2023) - [j5]Seok-Jun Bu, Sung-Bae Cho:
Triplet-trained graph transformer with control flow graph for few-shot malware classification. Inf. Sci. 649: 119598 (2023) - [c25]Seok-Jun Bu, Sung-Bae Cho:
Phishing URL Detection with Prototypical Neural Network Disentangled by Triplet Sampling. CISIS-ICEUTE 2023: 132-143 - [c24]Seok-Jun Bu, Sung-Bae Cho:
A Causally Explainable Deep Learning Model with Modular Bayesian Network for Predicting Electric Energy Demand. HAIS 2023: 519-532 - 2022
- [j4]Gwang-Myong Go, Seok-Jun Bu, Sung-Bae Cho:
Insider attack detection in database with deep metric neural network with Monte Carlo sampling. Log. J. IGPL 30(6): 979-992 (2022) - [c23]Kyoung-Won Park, Seok-Jun Bu, Sung-Bae Cho:
Evolutionary Triplet Network of Learning Disentangled Malware Space for Malware Classification. HAIS 2022: 311-322 - [c22]Jaeil Park, Seok-Jun Bu, Sung-Bae Cho:
A Neuro-Symbolic AI System for Visual Question Answering in Pedestrian Video Sequences. HAIS 2022: 443-454 - 2021
- [c21]Seok-Jun Bu, Hyung-Jun Moon, Sung-Bae Cho:
Adversarial Signal Augmentation for CNN-LSTM to Classify Impact Noise in Automobiles. BigComp 2021: 60-64 - [c20]Seok-Jun Bu, Hae-Jung Kim:
Learning Disentangled Representation of Web Address via Convolutional-Recurrent Triplet Network for Classifying Phishing URLs. ICEIC 2021: 1-4 - [c19]Kyoung-Won Park, Seok-Jun Bu, Sung-Bae Cho:
Evolutionary Optimization of Neuro-Symbolic Integration for Phishing URL Detection. HAIS 2021: 88-100 - [c18]Seok-Jun Bu, Sung-Bae Cho:
Integrating Deep Learning with First-Order Logic Programmed Constraints for Zero-Day Phishing Attack Detection. ICASSP 2021: 2685-2689 - [c17]Kyoung-Won Park, Seok-Jun Bu, Sung-Bae Cho:
Learning Dynamic Connectivity with Residual-Attention Network for Autism Classification in 4D fMRI Brain Images. IDEAL 2021: 387-396 - [c16]Hyung-Jun Moon, Seok-Jun Bu, Sung-Bae Cho:
Directional Graph Transformer-Based Control Flow Embedding for Malware Classification. IDEAL 2021: 426-436 - [c15]Hyung-Jun Moon, Seok-Jun Bu, Sung-Bae Cho:
Mutagenic Prediction for Chemical Compound Discovery with Partitioned Graph Convolution Network. SOCO 2021: 578-587 - 2020
- [j3]Wonsup Shin, Seok-Jun Bu, Sung-Bae Cho:
3D-Convolutional Neural Network with Generative Adversarial Network and Autoencoder for Robust Anomaly Detection in Video Surveillance. Int. J. Neural Syst. 30(6): 2050034:1-2050034:15 (2020) - [j2]Seok-Jun Bu, Sung-Bae Cho:
A convolutional neural-based learning classifier system for detecting database intrusion via insider attack. Inf. Sci. 512: 123-136 (2020) - [c14]Gwang-Myong Go, Seok-Jun Bu, Sung-Bae Cho:
Detecting Intrusion via Insider Attack in Database Transactions by Learning Disentangled Representation with Deep Metric Neural Network. CISIS 2020: 460-469 - [c13]Gue-Hwan Nam, Seok-Jun Bu, Namu Park, Jae-Yong Seo, Hyeon-Cheol Jo, Won-Tae Jeong:
Data Augmentation Using Empirical Mode Decomposition on Neural Networks to Classify Impact Noise in Vehicle. ICASSP 2020: 731-735 - [c12]Seok-Jun Bu, Namu Park, Gue-Hwan Nam, Jae-Yong Seo, Sung-Bae Cho:
A Monte Carlo Search-Based Triplet Sampling Method for Learning Disentangled Representation of Impulsive Noise on Steering Gear. ICASSP 2020: 3057-3061 - [c11]Hyung-Jun Moon, Seok-Jun Bu, Sung-Bae Cho:
Learning Disentangled Representation of Residential Power Demand Peak via Convolutional-Recurrent Triplet Network. ICDM (Workshops) 2020: 757-761 - [c10]Gwang-Myong Go, Seok-Jun Bu, Sung-Bae Cho:
A Deep Metric Neural Network with Disentangled Representation for Detecting Smartphone Glass Defects. IDEAL (2) 2020: 485-494 - [c9]Seok-Jun Bu, Sung-Bae Cho:
Automated Learning of In-vehicle Noise Representation with Triplet-Loss Embedded Convolutional Beamforming Network. IDEAL (2) 2020: 507-515
2010 – 2019
- 2019
- [c8]Seok-Jun Bu, Sung-Bae Cho:
Classifying In-vehicle Noise from Multi-channel Sound Spectrum by Deep Beamforming Networks. IEEE BigData 2019: 3545-3552 - [c7]Seok-Jun Bu, Sung-Bae Cho:
Genetic Algorithm-Based Deep Learning Ensemble for Detecting Database Intrusion via Insider Attack. HAIS 2019: 145-156 - [c6]Gwang-Myong Go, Seok-Jun Bu, Sung-Bae Cho:
A Deep Learning-Based Surface Defect Inspection System for Smartphone Glass. IDEAL (1) 2019: 375-385 - [i1]Wonsup Shin, Seok-Jun Bu, Sung-Bae Cho:
Automatic Financial Trading Agent for Low-risk Portfolio Management using Deep Reinforcement Learning. CoRR abs/1909.03278 (2019) - 2018
- [j1]Jin-Young Kim, Seok-Jun Bu, Sung-Bae Cho:
Zero-day malware detection using transferred generative adversarial networks based on deep autoencoders. Inf. Sci. 460-461: 83-102 (2018) - [c5]Jin-Young Kim, Seok-Jun Bu, Sung-Bae Cho:
Hybrid Deep Learning Based on GAN for Classifying BSR Noises from Invehicle Sensors. HAIS 2018: 27-38 - [c4]Seok-Jun Bu, Sung-Bae Cho:
A Hybrid Deep Learning System of CNN and LRCN to Detect Cyberbullying from SNS Comments. HAIS 2018: 561-572 - [c3]Seok-Jun Bu, Sung-Bae Cho:
Learning Optimal Q-Function Using Deep Boltzmann Machine for Reliable Trading of Cryptocurrency. IDEAL (1) 2018: 468-480 - 2017
- [c2]Seok-Jun Bu, Sung-Bae Cho:
A Hybrid System of Deep Learning and Learning Classifier System for Database Intrusion Detection. HAIS 2017: 615-625 - [c1]Jin-Young Kim, Seok-Jun Bu, Sung-Bae Cho:
Malware Detection Using Deep Transferred Generative Adversarial Networks. ICONIP (1) 2017: 556-564
Coauthor Index
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last updated on 2024-12-02 22:28 CET by the dblp team
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