Search Results for author:
Found 7 papers, 0 papers with code
Quantum Visual Feature Encoding Revisited
Although quantum machine learning has been introduced for a while, its applications in computer vision are still limited.
QClusformer: A Quantum Transformer-based Framework for Unsupervised Visual Clustering
In addition, we present QClusformer, a variant based on the Transformer architecture, tailored for unsupervised vision clustering tasks.
BRACTIVE: A Brain Activation Approach to Human Visual Brain Learning
Our experiments demonstrate that BRACTIVE effectively identifies person-specific regions of interest, such as face and body-selective areas, aligning with neuroscience findings and indicating potential applicability to various object categories.
Brainformer: Mimic Human Visual Brain Functions to Machine Vision Models via fMRI
This loss function mimics brain activity patterns from these regions in the deep neural network using fMRI data.
Quantum Vision Clustering
Unsupervised visual clustering has garnered significant attention in recent times, aiming to characterize distributions of unlabeled visual images through clustering based on a parameterized appearance approach.
UTOPIA: Unconstrained Tracking Objects without Preliminary Examination via Cross-Domain Adaptation
Then, a new cross-domain MOT adaptation from existing datasets is proposed without any pre-defined human knowledge in understanding and modeling objects.
Two-Dimensional Quantum Material Identification via Self-Attention and Soft-labeling in Deep Learning
In this work, we present a novel method to tackle the problem of missing annotation in instance segmentation in 2D quantum material identification.
