434 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- 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
6 papers · 1 filter
Elastic properties of nuclear pasta in neutron-star crusts
Cheng-Jun Xia, Toshiki Maruyama, Nobutoshi Yasutake +2
Based on the relativistic mean field (RMF) model with Thomas-Fermi approximation, we investigate the elastic properties of neutron star matter. The elastic constants are estimated…
Precompactness in matrix weighted Bourgain-Morrey spaces
Tengfei Bai, Jingshi Xu
In this paper, we introduce matrix weighted Bourgain-Morrey spaces and obtain two sufficient conditions for precompact sets in matrix weighted Bourgain-Morrey spaces. We prove that…
-Matrix Presentation of Quantum Affine Superalgebra for Type
Xianghua Wu, Hongda Lin, Honglian Zhang
In our preceding research, we introduced the Drinfeld presentation of the quantum affine superalgebra associated to the orthosymplectic Lie superalgebra f…
Digital Twin-Empowered Task Assignment in Aerial MEC Network: A Resource Coalition Cooperation Approach with Generative Model
Xin Tang, Qian Chen, Rong Yu +1
To meet the demands for ubiquitous communication and temporary edge computing in 6G networks, aerial mobile edge computing (MEC) networks have been envisioned as a new paradigm. Ho…
CrossMatch: Enhance Semi-Supervised Medical Image Segmentation with Perturbation Strategies and Knowledge Distillation
Bin Zhao, Chunshi Wang, Shuxue Ding
Semi-supervised learning for medical image segmentation presents a unique challenge of efficiently using limited labeled data while leveraging abundant unlabeled data. Despite adva…
Gland Segmentation Via Dual Encoders and Boundary-Enhanced Attention
Huadeng Wang, Jiejiang Yu, Bingbing Li +4
Accurate and automated gland segmentation on pathological images can assist pathologists in diagnosing the malignancy of colorectal adenocarcinoma. However, due to various gland sh…