A5101838233- User Authentication and Security Systems
- Internet Traffic Analysis and Secure E-voting
- Advanced Database Systems and Queries
- Reinforcement Learning in Robotics
- Advanced Bandit Algorithms Research
- Neurological Disease Mechanisms and Treatments
- Advanced Control Systems Optimization
- Machine Learning in Healthcare
- Data Visualization and Analytics
- Network Security and Intrusion Detection
- Semantic Web and Ontologies
- Biometric Identification and Security
- Domain Adaptation and Few-Shot Learning
- Brain Tumor Detection and Classification
- Advanced Neural Network Applications
- Remote-Sensing Image Classification
- Face recognition and analysis
- Topic Modeling
- Advanced Authentication Protocols Security
- Text and Document Classification Technologies
- Sentiment Analysis and Opinion Mining
- Bayesian Methods and Mixture Models
- Pelvic and Acetabular Injuries
- Chronic Disease Management Strategies
- Cryptography and Data Security
Shaanxi Provincial People's Hospital
2023
Shanxi Medical University
2023
Shenzhen Institutes of Advanced Technology
2023
Chinese Academy of Sciences
2023
Changshu Institute of Technology
2021-2023
Auckland University of Technology
2016-2020
Peking University
2019
The acquisition of global context and boundary information is crucial for the semantic segmentation remote sensing (RS) images. In contrast to convolutional neural networks (CNNs), transformers exhibit superior performance in modeling shape feature encoding, which provides a novel avenue obtaining information. However, current methods fail effectively leverage these distinctive advantages transformers. To address this issue, we propose single encoder dual decoders architecture called...
For most current sentiment analysis models, it is difficult to capture the complex semantic and grammatical information in text, they are not fully applicable of student sentiments. A novel text model using convolutional neural network with bidirectional gated recurrent unit an attention mechanism, called CNN-BiGRU-AT model, proposed. Firstly, divided into multiple sentences, (CNN) used extract n-gram different granularities from each sentence construct a sentence-level feature...
This study intends to build an artificial intelligence model for obstetric cesarean section surgery evaluate the intraoperative blood transfusion volume before operation, and compare prediction results with actual accuracy of red cell in obstetrics. The advantages disadvantages demand identification high-risk groups provide data support improvement suggestions realization accurate management patients during perioperative period.Using a machine learning algorithm, was trained. differences...
Objective Cerebral white matter hyperintensity can lead to cerebral small vessel disease, MRI images in the brain are used assess degree of pathological changes regions. In this paper, we propose a framework for automatic 3D segmentation based on address problems low accuracy and inhomogeneity segmentation. We explored correlation analyses cognitive assessment parameters multiple comparison investigate differences volume among three states, Dementia, MCI NCI. The study between coefficients...
Healthcare has been one of the most important issues in modern society. However, expenditure on healthcare is always a high burden for both individuals and countries. Aiming to take full advantage limited budget expenditure, many medical institutions resort estimate future cost carefully decide their spending plans. This enlightens us that accurate prediction contributes effective utilization resources. In this paper, we propose system crowd with co-existing conditions. We analyze diagnoses...