6 citations · 15 across the 11 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…