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In this paper, we propose a novel method to find characteristic landmarks onancient Roman imperial coins using deep convolutional neural network models(CNNs). We formulate an optimization problem to discover class-specific regionswhile guaranteeing specific controlled loss of accuracy. Analysis onvisualization of the discovered region confirms that not only can the proposedmethod successfully find a set of characteristic regions per class, but alsothe discovered region is consistent with human expert annotations. We alsopropose a new framework to recognize the Roman coins which exploitshierarchical structure of the ancient Roman coins using the state-of-the-artclassification power of the CNNs adopted to a new task of coin classification.Experimental results show that the proposed framework is able to effectivelyrecognize the ancient Roman coins. For this research, we have collected a newRoman coin dataset where all coins are annotated and consist of observe (head)and reverse (tail) images.

Discovering Characteristic Landmarks on Ancient Coins using Convolutional Networks