Ancient numismatics, the study of ancient coins, has in recent years become an attractive
domain for the application of computer vision and machine learning. Though rich in research …

We present a vision-based approach to ancient coins' identification. The approach is a two-
stage procedure. In the first stage an invariant shape description of the coin edge is …

We propose a holistic system to classify ancient Roman Republican coins based on their
reverse-side motifs. The bag-of-visual-words (BoW) model is enriched with spatial …

In this paper, we build upon the idea of using robust dense correspondence estimation for
exemplar-based image classification and adapt it to the problem of ancient coin …

Classification of ancient coins is a substantial part of numismatic research which needs a
large amount of expert knowledge due to the high number of classes to be considered. In …

This paper presents an automatic image-based ancient coin classification method that
adopts the recently proposed SIFT flow method in order to assess the similarity of coin …

We investigate object recognition and classification in a setting with a large number of
classes as well as recognition and identification of individual objects of high similarity. Real …

The assessment of forensic photographs often requires the calibration of the resolution of
the image so that accurate measurements can be taken of crime-scene exhibits or latent …

We propose to perform image-based ancient coin classification by recognizing symbols
minted on the reverse side of coins. Dense sampling based bag-of-visual-words model is …

Incorporating the spatial information of visual words enhances the performance of the well-
known bag-of-visual words (BoVWs) model for problems like object category recognition …