A5093041588- Brain Tumor Detection and Classification
- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
- Underwater Acoustics Research
- Remote Sensing and Land Use
- Advanced Authentication Protocols Security
- Remote-Sensing Image Classification
- Reservoir Engineering and Simulation Methods
- Remote Sensing in Agriculture
- Embedded Systems Design Techniques
- Advanced Malware Detection Techniques
- Neural Networks and Applications
- Time Series Analysis and Forecasting
Central South University
2023-2024
In modern healthcare, the precision of medical image segmentation holds immense significance for diagnosis and treatment planning. Deep learning techniques, such as CNNs, UNETs, Transformers, have revolutionized this field by automating previously labor-intensive manual processes. However, challenges like intricate structures indistinct features persist, leading to accuracy issues. Researchers are diligently addressing these further unlock potential in healthcare transformation. To enhance...
Abstract The field of medical image segmentation, particularly in the context brain tumor delineation, plays an instrumental role aiding healthcare professionals with diagnosis and accurate lesion quantification. Recently, Convolutional Neural Networks (CNNs) have demonstrated substantial efficacy a range computer vision tasks. However, notable limitation CNNs lies their inadequate capability to encapsulate global distal semantic information effectively. In contrast, advent Transformers,...
Given the increasingly serious security threats faced by embedded systems, an analysis has been conducted on characteristics and vulnerabilities of systems. Detailed discussions are provided systems from two major aspects: hardware-based attacks such as side-channel attacks, hardware Trojans, fault injection, microprobes, reverse engineering, software aimed at damaging, tampering, stealing. The includes existing measures both domestically internationally, highlighting their shortcomings....