Abstract: A method for evaluating (50) the health state of an anatomical element of an animal in a slaughtering plant provided with an image acquisition device. The evaluation method comprises the steps of: verifying the presence of the anatomical element; acquiring the image of the anatomical element; processing (S4) the image of the anatomical element through Deep Learning techniques, generating a lesion image representing lesioned portions of the anatomical element, and a number of processed images, each representing a corresponding non-lesioned anatomical area of the animal; for each of the lesioned portions and for each of the non-lesioned anatomical areas, determining a corresponding quantity indicative of the probability that said lesioned portion corresponds to said non-lesioned anatomical area; determining a score indicative of the health state of the anatomical element, depending on the determined quantities.

Abstract: A generative system for the creation of digital images for printing on design surfaces comprises a training dataset comprising a plurality of sample images for printing on design surfaces, a generative adversarial network comprising a generator and a discriminator, wherein the generator receives noise at input and is trained to generate at output starting from the noise a new artificially generated image adapted to be used for printing on design surfaces, and wherein the discriminator receives at input the new artificially generated image and is trained to compare and distinguish the new image generated by the sample images of the training dataset.

Abstract: A method for evaluating (50) the health state of an anatomical element of an animal in a slaughtering plant provided with an image acquisition device. The evaluation method comprises the steps of: verifying the presence of the anatomical element; acquiring the image of the anatomical element; processing (S4) the image of the anatomical element through Deep Learning techniques, generating a lesion image representing lesioned portions of the anatomical element, and a number of processed images, each representing a corresponding non-lesioned anatomical area of the animal; for each of the lesioned portions and for each of the non-lesioned anatomical areas, determining a corresponding quantity indicative of the probability that said lesioned portion corresponds to said non-lesioned anatomical area; determining a score indicative of the health state of the anatomical element, depending on the determined quantities.