249 citations · 321 across the 38 of their papers we have counts for
18 papers · 1 filter
Situation-Aware Deep Reinforcement Learning for Autonomous Nonlinear Mobility Control in Cyber-Physical Loitering Munition Systems
Hyunsoo Lee, Soohyun Park, Won Joon Yun +2
According to the rapid development of drone technologies, drones are widely used in many applications including military domains. In this paper, a novel situation-aware DRL- based…
Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Coding
Won Joon Yun, Jae Pyoung Kim, Hankyul Baek +4
While witnessing the noisy intermediate-scale quantum (NISQ) era and beyond, quantum federated learning (QFL) has recently become an emerging field of study. In QFL, each quantum c…
Projection Valued Measure-based Quantum Machine Learning for Multi-Class Classification
Won Joon Yun, Hankyul Baek, Joongheon Kim
In recent years, quantum machine learning (QML) has been actively used for various tasks, e.g., classification, reinforcement learning, and adversarial learning. However, these QML…
Software Simulation and Visualization of Quantum Multi-Drone Reinforcement Learning
Chanyoung Park, Jae Pyoung Kim, Won Joon Yun +3
Quantum machine learning (QML) has received a lot of attention according to its light training parameter numbers and speeds; and the advances of QML lead to active research on quan…
Quantum Split Neural Network Learning using Cross-Channel Pooling
Won Joon Yun, Hankyul Baek, Joongheon Kim
In recent years, the field of quantum science has attracted significant interest across various disciplines, including quantum machine learning, quantum communication, and quantum…
3D Scalable Quantum Convolutional Neural Networks for Point Cloud Data Processing in Classification Applications
Hankyul Baek, Won Joon Yun, Joongheon Kim
With the beginning of the noisy intermediate-scale quantum (NISQ) era, a quantum neural network (QNN) has recently emerged as a solution for several specific problems that classica…
Cooperative Multi-Agent Deep Reinforcement Learning for Reliable and Energy-Efficient Mobile Access via Multi-UAV Control
Chanyoung Park, Soohyun Park, Soyi Jung +2
This paper addresses a novel multi-agent deep reinforcement learning (MADRL)-based positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration (i.e., UAVs work…
Self-Configurable Stabilized Real-Time Detection Learning for Autonomous Driving Applications
Won Joon Yun, Soohyun Park, Joongheon Kim +1
Guaranteeing real-time and accurate object detection simultaneously is paramount in autonomous driving environments. However, the existing object detection neural network systems a…
FV-Train: Quantum Convolutional Neural Network Training with a Finite Number of Qubits by Extracting Diverse Features
Hankyul Baek, Won Joon Yun, Joongheon Kim
Quantum convolutional neural network (QCNN) has just become as an emerging research topic as we experience the noisy intermediate-scale quantum (NISQ) era and beyond. As convolutio…
Spatio-Temporal Attack Course-of-Action (COA) Search Learning for Scalable and Time-Varying Networks
Haemin Lee, Seok Bin Son, Won Joon Yun +3
One of the key topics in network security research is the autonomous COA (Couse-of-Action) attack search method. Traditional COA attack search methods that passively search for att…
Scalable Quantum Convolutional Neural Networks
Hankyul Baek, Won Joon Yun, Joongheon Kim
With the beginning of the noisy intermediate-scale quantum (NISQ) era, quantum neural network (QNN) has recently emerged as a solution for the problems that classical neural networ…
Quantum Multi-Agent Meta Reinforcement Learning
Won Joon Yun, Jihong Park, Joongheon Kim
Although quantum supremacy is yet to come, there has recently been an increasing interest in identifying the potential of quantum machine learning (QML) in the looming era of pract…
Slimmable Quantum Federated Learning
Won Joon Yun, Jae Pyoung Kim, Soyi Jung +3
Quantum federated learning (QFL) has recently received increasing attention, where quantum neural networks (QNNs) are integrated into federated learning (FL). In contrast to the ex…
Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Design
Won Joon Yun, Yunseok Kwak, Jae Pyoung Kim +4
In recent years, quantum computing (QC) has been getting a lot of attention from industry and academia. Especially, among various QC research topics, variational quantum circuit (V…
SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks
Won Joon Yun, Yunseok Kwak, Hankyul Baek +5
Federated learning (FL) is a key enabler for efficient communication and computing, leveraging devices' distributed computing capabilities. However, applying FL in practice is chal…
Quantum Distributed Deep Learning Architectures: Models, Discussions, and Applications
Yunseok Kwak, Won Joon Yun, Jae Pyoung Kim +4
Although deep learning (DL) has already become a state-of-the-art technology for various data processing tasks, data security and computational overload problems often arise due to…
Two-stage architectural fine-tuning with neural architecture search using early-stopping in image classification
Youngkee Kim, Won Joon Yun, Youn Kyu Lee +2
In many deep neural network (DNN) applications, the difficulty of gathering high-quality data in the industry field hinders the practical use of DNN. Thus, the concept of transfer…
Cooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control
Won Joon Yun, Soohyun Park, Joongheon Kim +4
CCTV-based surveillance using unmanned aerial vehicles (UAVs) is considered a key technology for security in smart city environments. This paper creates a case where the UAVs with…