Generative adversarial networks (GANs) have been extensively studied in the past few years. Arguably their most significant impact has area of computer vision where great advances made challenges such as plausible image generation, image-to-image translation, facial attribute manipulation, and similar domains. Despite successes achieved to date, applying GANs real-world problems still poses cha...

This paper presents a computer-vision-based methodology for automatic image-based classification of 2042 training images and 284 unseen (test) divided into 68 categories gemstones. A series feature extraction techniques (33 including colour histograms in the RGB, HSV CIELAB space, local binary pattern, Haralick texture grey-level co-occurrence matrix properties) were used combination with diffe...