434 citations
- Chinese Academy of SciencesCN16 papers
- Shanghai Astronomical ObservatoryCN12 papers
- Sun Yat-sen UniversityCN11 papers
- École de Technologie SupérieureCA10 papers
- Guangxi Key Laboratory of Optoelectronic Information ProcessingCN10 papers
- Guilin University of TechnologyCN8 papers
- Taibah UniversitySA6 papers
- Tsinghua UniversityCN6 papers
- Centre National de la Recherche ScientifiqueFR5 papers
- Dongguan University of TechnologyCN5 papers
- Harbin Institute of TechnologyCN5 papers
- Peng Cheng LaboratoryCN5 papers
147 papers
Estimating the peak energy of Swift gamma-ray bursts using supervised machine learning
Wan-Peng Sun, Si-Yuan Zhu, Da-Ling Ma +1
Gamma-ray bursts (GRBs) are among the most energetic explosive phenomena in the Universe, and their peak energy () is a key physical quantity for understanding the promp…
Quantum Semantic Communication Beyond the Shannon-Wyner Channel Capacity
Min Wang, Gui-Fa Zhu, Guo-Fei Long +5
Quantum Secure Direct Communication (QSDC), a paradigm-shifting breakthrough in quantum communication, exploits quantum states for unmediated information transmission. Rooted in th…
Eigen-microstate Signatures of Criticality in Relativistic Heavy-Ion Collisions
Ranran Guo, Jin Wu, Mingmei Xu +4
We develop the eigen-microstate framework as a new approach to identify criticality in relativistic heavy-ion collisions. We construct the original microstate, defined as the final…
MoTiC: Momentum Tightness and Contrast for Few-Shot Class-Incremental Learning
Zeyu He, Shuai Huang, Yuwu Lu +1
Few-Shot Class-Incremental Learning (FSCIL) must contend with the dual challenge of learning new classes from scarce samples while preserving old class knowledge. Existing methods…
Towards a Transparent and Interpretable AI Model for Medical Image Classifications
Binbin Wen, Yihang Wu, Tareef Daqqaq +1
The integration of artificial intelligence (AI) into medicine is remarkable, offering advanced diagnostic and therapeutic possibilities. However, the inherent opacity of complex AI…
Enhancing Dual Network Based Semi-Supervised Medical Image Segmentation with Uncertainty-Guided Pseudo-Labeling
Yunyao Lu, Yihang Wu, Ahmad Chaddad +2
Despite the remarkable performance of supervised medical image segmentation models, relying on a large amount of labeled data is impractical in real-world situations. Semi-supervis…