1. A computer-implemented method for classifying an object occurring in a sequence of images, comprising: tracking, by a processor, the object through the sequence of images; generating, by the processor and from the sequence of images, a set of temporally distributed image crops including the object; feeding, by the processor, the set of image crops to an artificial neural network trained for classifying an object; determining, by the artificial neural network, a classification result for each image crop; determining, by the processor, a quality measure of each classification result, wherein the quality measure is determined based on one or more of: a confidence measure of a classification vector output from the artificial neural network, and a resolution of the image crop; weighting, by the processor, the classification result for each image crop by its quality measure; and determining, by the processor, an object class for the object by combining the weighted output from the artificial neural network for the set of images.