249 citations · 291 across the 31 of their papers we have counts for
19 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…
Neural Architectural Nonlinear Pre-Processing for mmWave Radar-based Human Gesture Perception
Hankyul Baek, Yoo Jeong, Ha +3
In modern on-driving computing environments, many sensors are used for context-aware applications. This paper utilizes two deep learning models, U-Net and EfficientNet, which consi…
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…
Multi-Agent Deep Reinforcement Learning for Efficient Passenger Delivery in Urban Air Mobility
Chanyoung Park, Soohyun Park, Gyu Seon Kim +3
It has been considered that urban air mobility (UAM), also known as drone-taxi or electrical vertical takeoff and landing (eVTOL), will play a key role in future transportation. By…
Age-of-Information Aware Contents Caching and Distribution for Connected Vehicles
Soohyun Park, Chanyoung Park, Soyi Jung +2
To support rapid and accurate autonomous driving services, road environment information, which is difficult to obtain through vehicle sensors themselves, is collected and utilized…
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…
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…
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…
Search Space Adaptation for Differentiable Neural Architecture Search in Image Classification
Youngkee Kim, Soyi Jung, Minseok Choi +1
As deep neural networks achieve unprecedented performance in various tasks, neural architecture search (NAS), a research field for designing neural network architectures with autom…
Tutorial on Course-of-Action (COA) Attack Search Methods in Computer Networks
Seok Bin Son, Soohyun Park, Haemin Lee +3
In the literature of modern network security research, deriving effective and efficient course-of-action (COA) attach search methods are of interests in industry and academia. As t…
Quality-Aware Real-Time Augmented Reality Visualization under Delay Constraints
Rhoan Lee, Soohyun Park, Soyi Jung +1
Augmented reality (AR) is one of emerging applications in modern multimedia systems research. Due to intensive time-consuming computations for AR visualization in mobile devices, q…
AoI-Aware Markov Decision Policies for Caching
Soohyun Park, Soyi Jung, Minseok Choi +1
We consider a scenario that utilizes road side units (RSUs) as distributed caches in connected vehicular networks. The goal of the use of caches in our scenario is for rapidly prov…
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…
Feasibility Study of Multi-Site Split Learning for Privacy-Preserving Medical Systems under Data Imbalance Constraints in COVID-19, X-Ray, and Cholesterol Dataset
Yoo Jeong Ha, Gusang Lee, Minjae Yoo +3
It seems as though progressively more people are in the race to upload content, data, and information online; and hospitals haven't neglected this trend either. Hospitals are now a…
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…