Publications (31)
A Novel Automation-Assisted Cervical Cancer Reading Method Based on Convolutional Neural Network
Yao Xiang, Wanxin Sun, Changli Pan +3
While most previous automation-assisted reading methods can improve efficiency, their performance often relies on the success of accurate cell segmentation and hand-craft feature e…
A Probability Distribution and Location-aware ResNet Approach for QoS Prediction
Wenyan Zhang, Ling Xu, Meng Yan +2
In recent years, the number of online services has grown rapidly, invoke the required services through the cloud platform has become the primary trend. How to help users choose and…
The - and -wave fully charmed tetraquark states and their radial excitations
Guo-Liang Yu, Zhen-Yu Li, Zhi-Gang Wang +2
Inspired by recent progresses in observations of the fully charmed tetraquark states by LHCb, CMS, and ATLAS Collaborations, we perform a systematic study of the ground states and…
Fixing Function-Level Code Generation Errors for Foundation Large Language Models
Hao Wen, Yueheng Zhu, Chao Liu +3
Function-level code generation leverages foundation Large Language Models (LLMs) to automatically produce source code with expected functionality. It has been widely investigated a…
Unified Abstract Syntax Tree Representation Learning for Cross-Language Program Classification
Kesu Wang, Meng Yan, He Zhang +1
Program classification can be regarded as a high-level abstraction of code, laying a foundation for various tasks related to source code comprehension, and has a very wide range of…
Comparison-Based Convolutional Neural Networks for Cervical Cell/Clumps Detection in the Limited Data Scenario
Yixiong Liang, Zhihong Tang, Meng Yan +3
Automated detection of cervical cancer cells or cell clumps has the potential to significantly reduce error rate and increase productivity in cervical cancer screening. However, mo…