Abstract: The disclosure relates to methods and systems for carcass processing options based on a primal/subprimal weights and yield training module. In one embodiment, the methods and systems disclosed herein use automated methods to process image data, process the image data using one or more trained modules, and determine carcass processing options based on an estimated weight calculation output from the trained modules, without using a scale-based weight measurement as an input.

Abstract: The present invention relates to the training of a convolutional neural network by a set of automatically generated simulated training data for use in a machine vision system for identifying fiducial tags associated with entities. Four-character fiducial tags are randomly generated or selected and then randomly transformed and superimposed on images to generate a set of simulated training data to be fed into a convolutional neural network to train the network model. The trained convolutional neural network is used to identify fiducial tags disposed on entities in real-world images and video.

Abstract: The present invention relates to the automated monitoring of animals, in particular livestock animals such as swine, for the identification or determination of particular physical characteristics or conditions that may be used to predict one or more phenotypes or health outcomes for the each of the animals. Systems and methods are provided for the non-subjective and automatic identification or prediction of one or more phenotypes, such as weight or gait, based on computer-vision system analysis of video or image data capture of an animal retaining space in a commercial farming operation. The predicted or identified phenotypes are used to predict one or more health outcomes or scores for an animal.

Abstract: A system and methods to evaluate and monitor the healing progress of a wound. At least two optical imaging devices are mounted on a support device in order to capture images. The images are resolved in order to be matched to create a depth map of the object. The depth map can be analyzed to obtain data, such as the length, width, and depth of the wound and the area and volume of the wound.