Canine age classification using Deep Learning as a step toward preventive medicine in animals

Abstract

The main goal of this work was to implement a reliable machine learning algorithm that can classify a dog's age given only a photograph of its face. The problem, which seems simple for humans, presents itself as very difficult for the machine learning algorithms due to differences in facial features among the dog population. As convolutional neural networks (CNNs) performed poorly in this problem, the authors took another approach of creating novel architecture consisting of a combination of CNN and vision transformer (ViT) and examining the age of the dogs separately for every breed. Authors achieved better results than those in initial works covering the problem.