Abstract: A computer application may aim to identify first and second “matching” objects. The matching method cannot necessarily be based on how visually similar the two objects are to each other because two matching objects might be different and/or be visually different. Moreover, the images of the objects to be matched might not necessarily have metadata to assist in the matching. In some embodiments, a machine learning model may be trained using a set of digital images, each including two or more matching objects. Triplet loss training may be used, and each triplet may include: an image of a first object extracted from a first image, an image of an object that is visually similar to an image of a second object extracted from the first image, and an image of a third object extracted from a different image.