Seok-Jun Buu

Orcid: 0000-0002-3940-3611

According to our database1, Seok-Jun Buu authored at least 38 papers between 2017 and 2024.

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

Timeline

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Bibliography

2024
Deep Generative Replay With Denoising Diffusion Probabilistic Models for Continual Learning in Audio Classification.
IEEE Access, 2024

Disentangled Prototypical Convolutional Network for Few-Shot Learning in In-Vehicle Noise Classification.
IEEE Access, 2024

Graph Anomaly Detection With Disentangled Prototypical Autoencoder for Phishing Scam Detection in Cryptocurrency Transactions.
IEEE Access, 2024

Disentangled Prototype-Guided Dynamic Memory Replay for Continual Learning in Acoustic Signal Classification.
IEEE Access, 2024

Anchor-Net: Distance-Based Self-Supervised Learning Model for Facial Beauty Prediction.
IEEE Access, 2024

2023
Triplet-trained graph transformer with control flow graph for few-shot malware classification.
Inf. Sci., November, 2023

Malware classification with disentangled representation learning of evolutionary triplet network.
Neurocomputing, October, 2023

A graph convolution network with subgraph embedding for mutagenic prediction in aromatic hydrocarbons.
Neurocomputing, April, 2023

A Causally Explainable Deep Learning Model with Modular Bayesian Network for Predicting Electric Energy Demand.
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023

Phishing URL Detection with Prototypical Neural Network Disentangled by Triplet Sampling.
Proceedings of the International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023), 2023

2022
Insider attack detection in database with deep metric neural network with Monte Carlo sampling.
Log. J. IGPL, 2022

A Neuro-Symbolic AI System for Visual Question Answering in Pedestrian Video Sequences.
Proceedings of the Hybrid Artificial Intelligent Systems - 17th International Conference, 2022

Evolutionary Triplet Network of Learning Disentangled Malware Space for Malware Classification.
Proceedings of the Hybrid Artificial Intelligent Systems - 17th International Conference, 2022

2021
Mutagenic Prediction for Chemical Compound Discovery with Partitioned Graph Convolution Network.
Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021

Learning Dynamic Connectivity with Residual-Attention Network for Autism Classification in 4D fMRI Brain Images.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2021, 2021

Directional Graph Transformer-Based Control Flow Embedding for Malware Classification.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2021, 2021

Integrating Deep Learning with First-Order Logic Programmed Constraints for Zero-Day Phishing Attack Detection.
Proceedings of the IEEE International Conference on Acoustics, 2021

Evolutionary Optimization of Neuro-Symbolic Integration for Phishing URL Detection.
Proceedings of the Hybrid Artificial Intelligent Systems - 16th International Conference, 2021

Learning Disentangled Representation of Web Address via Convolutional-Recurrent Triplet Network for Classifying Phishing URLs.
Proceedings of the International Conference on Electronics, Information, and Communication, 2021

Adversarial Signal Augmentation for CNN-LSTM to Classify Impact Noise in Automobiles.
Proceedings of the IEEE International Conference on Big Data and Smart Computing, 2021

2020
A convolutional neural-based learning classifier system for detecting database intrusion via insider attack.
Inf. Sci., 2020

3D-Convolutional Neural Network with Generative Adversarial Network and Autoencoder for Robust Anomaly Detection in Video Surveillance.
Int. J. Neural Syst., 2020

A Deep Metric Neural Network with Disentangled Representation for Detecting Smartphone Glass Defects.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2020, 2020

Automated Learning of In-vehicle Noise Representation with Triplet-Loss Embedded Convolutional Beamforming Network.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2020, 2020

Learning Disentangled Representation of Residential Power Demand Peak via Convolutional-Recurrent Triplet Network.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

Data Augmentation Using Empirical Mode Decomposition on Neural Networks to Classify Impact Noise in Vehicle.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

A Monte Carlo Search-Based Triplet Sampling Method for Learning Disentangled Representation of Impulsive Noise on Steering Gear.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Detecting Intrusion via Insider Attack in Database Transactions by Learning Disentangled Representation with Deep Metric Neural Network.
Proceedings of the 13th International Conference on Computational Intelligence in Security for Information Systems, 2020

2019
Automatic Financial Trading Agent for Low-risk Portfolio Management using Deep Reinforcement Learning.
CoRR, 2019

A Deep Learning-Based Surface Defect Inspection System for Smartphone Glass.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2019, 2019

Genetic Algorithm-Based Deep Learning Ensemble for Detecting Database Intrusion via Insider Attack.
Proceedings of the Hybrid Artificial Intelligent Systems - 14th International Conference, 2019

Classifying In-vehicle Noise from Multi-channel Sound Spectrum by Deep Beamforming Networks.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
Zero-day malware detection using transferred generative adversarial networks based on deep autoencoders.
Inf. Sci., 2018

Learning Optimal Q-Function Using Deep Boltzmann Machine for Reliable Trading of Cryptocurrency.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

Hybrid Deep Learning Based on GAN for Classifying BSR Noises from Invehicle Sensors.
Proceedings of the Hybrid Artificial Intelligent Systems - 13th International Conference, 2018

A Hybrid Deep Learning System of CNN and LRCN to Detect Cyberbullying from SNS Comments.
Proceedings of the Hybrid Artificial Intelligent Systems - 13th International Conference, 2018

2017
Malware Detection Using Deep Transferred Generative Adversarial Networks.
Proceedings of the Neural Information Processing - 24th International Conference, 2017

A Hybrid System of Deep Learning and Learning Classifier System for Database Intrusion Detection.
Proceedings of the Hybrid Artificial Intelligent Systems - 12th International Conference, 2017


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