Abstract: Systems and methods for decision tree construction and update using quantum algorithms are disclosed. A method may include: receiving, by a classical computer program, a dataset comprising a plurality of training examples, each of the plurality of training examples having a plurality of features; loading, by a classical computer program, the dataset into a quantum accessible data structure; providing, by the classical computer program, the quantum accessible data structure to a quantum computer, wherein the quantum computer is configured to perform quantum estimation of a Pearson correlation coefficient on the dataset in the quantum accessible data structure to create a weighted dataset; clustering, by the classical computer program and the quantum computer, each of the plurality of training examples in the weighted dataset into one of a plurality of clusters; and selecting, by the classical computer program, a label for each of the plurality of clusters.

Abstract: Provided are methods, systems, and computer program products for image based LiDAR-camera synchronization. An example method may include: obtaining an image from an image sensor; detecting at least one edge of a pattern in the image, the pattern corresponding to at least one electromagnetic wave emitted from a rangefinder system; determining an offset between the pattern and the image based on the at least one edge of the pattern; determining the offset satisfies a synchronization threshold; and based on the determining the offset satisfies a synchronization threshold, adjusting a synchronization parameter of the image sensor or rangefinder system.