d-zhang3
d.zhang3
Recently Published
K-Means Photo Inpainting: A Simple Unsupervised Learning Approach
This paper applies K-Means clustering for patch-based image inpainting: it learns a texture dictionary from intact grayscale regions, then uses it to predict missing pixels. The method is computationally efficient, validated on sparse random damage, and performance is measured as corruption increases.
Association Rule Mining of Age-Specific Dental Treatment Patterns
An Unsupervised Learning Approach Using NHANES Data
Dimensionality Reduction for Art History: PCA-Based Color Signatures
Exploring Art Movements through Computational Color Analysis