Hilbert Curve

The Hilbert curve is a space-filling fractal curve renowned for its ability to map multi-dimensional data onto a one-dimensional space while preserving locality. Current research focuses on leveraging this property for improved efficiency in various applications, including distribution comparison using novel metrics like Hilbert curve projection distance, and enhancing machine learning models by incorporating Hilbert curve-based flattening techniques for feature maps. This ongoing work demonstrates the Hilbert curve's continued relevance in addressing challenges in areas such as computer vision, data indexing, and machine learning, particularly in handling high-dimensional data and improving computational efficiency.