Distance Measure

Distance measurement is a fundamental problem across numerous scientific disciplines, aiming to quantify the dissimilarity between data points or objects, enabling tasks like clustering, classification, and anomaly detection. Current research emphasizes developing efficient and effective distance measures tailored to specific data types, including those involving point clouds, time series, geometric graphs, and high-dimensional data, often leveraging algorithms like dynamic time warping, k-means clustering, and variations of the Earth Mover's Distance. These advancements are crucial for improving the accuracy and efficiency of various applications, ranging from automated agricultural practices and robotic navigation to pattern recognition and data analysis in diverse fields.