A5101978957- Poxvirus research and outbreaks
- Epilepsy research and treatment
- AI in cancer detection
- Manufacturing Process and Optimization
- Infrastructure Maintenance and Monitoring
- Image Processing Techniques and Applications
- Advanced Neural Network Applications
- Brain Tumor Detection and Classification
- Industrial Vision Systems and Defect Detection
- COVID-19 diagnosis using AI
- Bacillus and Francisella bacterial research
- ECG Monitoring and Analysis
- Advanced MRI Techniques and Applications
- Yersinia bacterium, plague, ectoparasites research
- EEG and Brain-Computer Interfaces
- Non-Invasive Vital Sign Monitoring
- Transplantation: Methods and Outcomes
- Heart Failure Treatment and Management
- Welding Techniques and Residual Stresses
- Lanthanide and Transition Metal Complexes
- Image Processing and 3D Reconstruction
- Herpesvirus Infections and Treatments
- Analytical Chemistry and Sensors
Shenyang Institute of Computing Technology (China)
2023-2024
Chinese Academy of Sciences
2023-2024
University of Chinese Academy of Sciences
2023-2024
University of Shanghai for Science and Technology
2023
Although semantic segmentation methods have made remarkable progress so far, their long inference process limits use in practical applications. Recently, some two-branch and three-branch real-time networks been proposed to improve accuracy by adding branches extract spatial or border information. For the design of extracting information branches, preserving high-resolution features loss guide are commonly used However, these approaches not most efficient. To solve problem, we extraction...
Due to the absence of more efficient diagnostic tools, spread mpox continues be unchecked. Although related studies have demonstrated high efficiency deep learning models in diagnosing mpox, key aspects such as model inference speed and parameter size always been overlooked. Herein, an ultrafast ultralight network named Fast‐MpoxNet is proposed. Fast‐MpoxNet, with only 0.27 m parameters, can process input images at 68 frames per second (FPS) on CPU. To detect subtle image differences...
High sensitivity and accuracy of heart failure biomarker, N-terminal prohormone brain natriuretic peptide (NT-proBNP), is critical for the early detection failure. However, traditional chemiluminescent (CL) probe still face challenges poor solubility, in particular, significant disappointing bioavailability, which profoundly limit its clinical applications. In this paper, we demonstrate functional CL acridinium ester (AE-2) NT-proBNP, through introducing a hydrophilic unit ensuring high...
Due to the absence of more efficient diagnostic tools, spread mpox continues be unchecked. Although related studies have demonstrated high efficiency deep learning models in diagnosing mpox, key aspects such as model inference speed and parameter size always been overlooked. Herein, an ultrafast ultralight network named Fast-MpoxNet is proposed. Fast-MpoxNet, with only 0.27M parameters, can process input images at 68 frames per second (FPS) on CPU. To detect subtle image differences optimize...
Recent studies have employed computer vision and convolutional neural network based methods to automate enhance the diagnosis on chest X-ray. However, these approaches demand significant computational resources other intricate techniques produce results.In order reduce model parameters improve diagnostic accuracy of COVID-19, we proposed a framework lightweight CNN transformer. This leverages two key components: MBConvFusion module mobile inverted bottleneck convolution block. By introducing...