Nikolay Sirakov

1. Introduction An important meta parameter in machine learning (ML) is the training set. For deep ML classifiers, extensive training datasets are required to achieve robust statistical results. If the large training sets also contain relatively high-resolution images, then the training process becomes extremely time-consuming.

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1. Introduction The number, sizes, and variety of image databases have grown in the last decade. These databases are generated to derive information and knowledge to support solutions to problems in medicine, science, security, and industry. Also, the demand for increasing accuracy when working with image databases is high and important. For example, face image databases usually contain hundreds of thousands of images.