Publications (12)
On the correlation measure of a family of commuting Hermitian operators with applications to particle densities of the quasi-free representations of the CAR and CCR
Eugene Lytvynov, Lin Mei
Let be a locally compact, second countable Hausdorff topological space. We consider a family of commuting Hermitian operators indexed by all measurable, relatively comp…
DatasetAgent: A Novel Multi-Agent System for Auto-Constructing Datasets from Real-World Images
Haoran Sun, Haoyu Bian, Shaoning Zeng +4
Common knowledge indicates that the process of constructing image datasets usually depends on the time-intensive and inefficient method of manual collection and annotation. Large m…
DMM: Disparity-guided Multispectral Mamba for Oriented Object Detection in Remote Sensing
Minghang Zhou, Tianyu Li, Chaofan Qiao +5
Multispectral oriented object detection faces challenges due to both inter-modal and intra-modal discrepancies. Recent studies often rely on transformer-based models to address the…
Multi-Granularity Mutual Refinement Network for Zero-Shot Learning
Ning Wang, Long Yu, Cong Hua +5
Zero-shot learning (ZSL) aims to recognize unseen classes with zero samples by transferring semantic knowledge from seen classes. Current approaches typically correlate global visu…
Robust High-Resolution Multi-Organ Diffusion MRI Using Synthetic-Data-Tuned Prompt Learning
Chen Qian, Haoyu Zhang, Junnan Ma +26
Clinical adoption of multi-shot diffusion-weighted magnetic resonance imaging (multi-shot DWI) for body-wide tumor diagnostics is limited by severe motion-induced phase artifacts f…
Formation and Evolution of Transient Prominence Bubbles Driven by Erupting Mini-filaments
Yilin Guo, Yijun Hou, Ting Li +6
Prominence bubbles, the dark arch-shaped "voids" below quiescent prominences, are generally believed to be caused by the interaction between the prominences and the slowly-emerging…
SkeletonContext: Skeleton-side Context Prompt Learning for Zero-Shot Skeleton-based Action Recognition
Ning Wang, Tieyue Wu, Naeha Sharif +5
Zero-shot skeleton-based action recognition aims to recognize unseen actions by transferring knowledge from seen categories through semantic descriptions. Most existing methods typ…
Bridging Vision and Language Concepts through Optimal Transport Semantic Flow
Chenyang Zhang, Anqi Dong, Guangming Zhu +4
Concept Bottleneck Models (CBMs) promise transparent reasoning by predicting through human-interpretable concepts, yet their effectiveness fundamentally depends on how well visual…
Intervening in Black Box: Concept Bottleneck Model for Enhancing Human Neural Network Mutual Understanding
Nuoye Xiong, Anqi Dong, Ning Wang +5
Recent advances in deep learning have led to increasingly complex models with deeper layers and more parameters, reducing interpretability and making their decisions harder to unde…
A Systematic Collection of Medical Image Datasets for Deep Learning
Johann Li, Guangming Zhu, Cong Hua +11
The astounding success made by artificial intelligence (AI) in healthcare and other fields proves that AI can achieve human-like performance. However, success always comes with cha…
Long-term Effects of Temperature Variations on Economic Growth: A Machine Learning Approach
Eugene Kharitonov, Oksana Zakharchuk, Lin Mei
This study investigates the long-term effects of temperature variations on economic growth using a data-driven approach. Leveraging machine learning techniques, we analyze global l…
A Study of Active Galactic Nuclei in Low Surface Brightness Galaxies with Sloan Digital Sky Survey Spectroscopy
Lin Mei, Weimin Yuan, Xiaobo Dong
Active galactic nuclei (AGN) in low surface brightness galaxies (LSBGs) have received little attention in previous studies. In this paper, we present detailed spectral analysis of…