Area of research
Geometry and Topology · Artificial Intelligence
Research interest
Research interests include Computer science, Artificial intelligence, Feature (linguistics), Osteoarthritis, Knee Joint, and Bronchoscopy.
Predicting joint space changes in knee osteoarthritis over 6 years: a combined model of TransUNet and XGBoost
An improved semantic segmentation algorithm for high-resolution remote sensing images based on DeepLabv3+
TDF-Net: Trusted Dynamic Feature Fusion Network for breast cancer diagnosis using incomplete multimodal ultrasound
Automated measurement and grading of knee cartilage thickness: a deep learning-based approach
Joint Lesion Detection and Classification of Breast Ultrasound Video via a Clinical Knowledge-Aware Framework
An accurate prediction for respiratory diseases using deep learning on bronchoscopy diagnosis images
PKDN: Prior Knowledge Distillation Network for bronchoscopy diagnosis
SDA-Net: Self-distillation driven deformable attentive aggregation network for thyroid nodule identification in ultrasound images