Machine learning process and method of targeted clustering based on single shot sampling

Abstract

A method for improving an accuracy of object classification, the method includes: (i) receiving, by a machine learning process, information regarding an environment of a vehicle; (ii) classifying, by the machine learning process, an object that is located within the environment of the vehicle to a certain class; wherein the machine learning process was trained by a training process to classify objects while avoiding false positive (FP) errors that are represented by different FP data sets that are fed to the machine learning process during the training process, the different FP data sets are associated with different classes; wherein for each class of the different classes, a FP data set that is associated with the class comprises FP data sub-sets that are associated with different objects that were mistakenly classified to the class; and outputting an outcome of the classification for use in navigating the vehicle.