Discovering characteristic landmarks on ancient coins using convolutional networks

We propose a novel method to find characteristic landmarks and recognize ancient Roman imperial coins using deep convolutional neural networks (CNNs) combined with expert-designed domain hierarchies. We first propose a new framework to recognize the Roman coin which exploits the hierarchical knowledge structure embedded in the coin domain, which we combine with the CNN-based category classifiers. We next formulate an optimization problem to discover class-specific salient coin regions. Analysis of discovered salient regions confirms that they are largely consistent with human expert annotations. Experimental results show that the proposed framework is able to effectively recognize the ancient Roman coins as well as successfully identify landmarks in a general fine-grained classification problem. For this research, we have collected a new Roman coin dataset where all coins are annotated and consist of obverse (head) and reverse (tail) images.