Article-Journal

We propose novel transfer functions for volumetric rendering of hand MRI data that improve visualization of complex hand anatomy while maintaining fine control over tissue appearance.

Using Wi-Fi data analytics and machine learning to quantify urban vibrancy at the street level, demonstrated through a case study of urban interventions in Shanghai while preserving user privacy.

Our SeisFormer model based on self-attention mechanism for real-time structural response prediction under seismic action for large-scale structures, achieving high accuracy and efficiency even with limited training data.

A real-time drone-based crack detection method that combines lightweight and high-precision algorithms with autonomous flight control for efficient building damage assessment.

A novel three-stage deep learning method for crack detection in high-resolution steel box girder images, combining patch-based CBAM ResNet-50 for localization, Attention U-Net for edge detection, and morphological operations for refinement.