6 citations · 15 across the 11 of their papers we have counts for
12 papers
QUACOD: Quantum Optimization via Coordinate Descent for Scalable Drone Scheduling
Van-Quang-Huy Nguyen, Hoang-Quan Nguyen, Samee U. Khan +2
Quantum computing has demonstrated its potential to solve various optimization problems, including drone scheduling, which is important not only for drone delivery but also for log…
QMoE: A Quantum Mixture of Experts Framework for Scalable Quantum Neural Networks
Hoang-Quan Nguyen, Xuan-Bac Nguyen, Sankalp Pandey +3
Quantum machine learning (QML) has emerged as a promising direction in the noisy intermediate-scale quantum (NISQ) era, offering computational and memory advantages by harnessing s…
QUADRO: A Hybrid Quantum Optimization Framework for Drone Delivery
James B. Holliday, Darren Blount, Hoang Quan Nguyen +2
Quantum computing holds transformative potential for optimizing large-scale drone fleet operations, yet its near-term limitations necessitate hybrid approaches blending classical a…
Quantum-Brain: Quantum-Inspired Neural Network Approach to Vision-Brain Understanding
Hoang-Quan Nguyen, Xuan-Bac Nguyen, Hugh Churchill +4
Vision-brain understanding aims to extract semantic information about brain signals from human perceptions. Existing deep learning methods for vision-brain understanding are usuall…
Hierarchical Quantum Control Gates for Functional MRI Understanding
Xuan-Bac Nguyen, Hoang-Quan Nguyen, Hugh Churchill +2
Quantum computing has emerged as a powerful tool for solving complex problems intractable for classical computers, particularly in popular fields such as cryptography, optimization…
Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
Hoang-Quan Nguyen, Xuan Bac Nguyen, Samuel Yen-Chi Chen +4
Parameterized Quantum Circuits (PQCs) have been acknowledged as a leading strategy to utilize near-term quantum advantages in multiple problems, including machine learning and comb…
Quantum Visual Feature Encoding Revisited
Xuan-Bac Nguyen, Hoang-Quan Nguyen, Hugh Churchill +2
Although quantum machine learning has been introduced for a while, its applications in computer vision are still limited. This paper, therefore, revisits the quantum visual encodin…
QClusformer: A Quantum Transformer-based Framework for Unsupervised Visual Clustering
Xuan-Bac Nguyen, Hoang-Quan Nguyen, Samuel Yen-Chi Chen +3
Unsupervised vision clustering, a cornerstone in computer vision, has been studied for decades, yielding significant outcomes across numerous vision tasks. However, these algorithm…
BRACTIVE: A Brain Activation Approach to Human Visual Brain Learning
Xuan-Bac Nguyen, Hojin Jang, Xin Li +3
The human brain is a highly efficient processing unit, and understanding how it works can inspire new algorithms and architectures in machine learning. In this work, we introduce a…
Brainformer: Mimic Human Visual Brain Functions to Machine Vision Models via fMRI
Xuan-Bac Nguyen, Xin Li, Pawan Sinha +2
Human perception plays a vital role in forming beliefs and understanding reality. A deeper understanding of brain functionality will lead to the development of novel deep neural ne…
Quantum Vision Clustering
Xuan Bac Nguyen, Hugh Churchill, Khoa Luu +1
Unsupervised visual clustering has garnered significant attention in recent times, aiming to characterize distributions of unlabeled visual images through clustering based on a par…
Two-Dimensional Quantum Material Identification via Self-Attention and Soft-labeling in Deep Learning
Xuan Bac Nguyen, Apoorva Bisht, Ben Thompson +3
In quantum machine field, detecting two-dimensional (2D) materials in Silicon chips is one of the most critical problems. Instance segmentation can be considered as a potential app…