9 citations · 22 across the 11 of their papers we have counts for
11 papers
Fast Quantum Convolutional Neural Networks for Low-Complexity Object Detection in Autonomous Driving Applications
Hankyul Baek, Donghyeon Kim, Joongheon Kim
Spurred by consistent advances and innovation in deep learning, object detection applications have become prevalent, particularly in autonomous driving that leverages various visua…
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…
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…
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…
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…
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…
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…
Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decoding
Hankyul Baek, Won Joon Yun, Soyi Jung +4
Mobile devices are indispensable sources of big data. Federated learning (FL) has a great potential in exploiting these private data by exchanging locally trained models instead of…
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
Hankyul Baek, Won Joon Yun, Yunseok Kwak +5
This paper aims to integrate two synergetic technologies, federated learning (FL) and width-adjustable slimmable neural network (SNN) architectures. FL preserves data privacy by ex…