Feature identification in archaeological fragments using families of algebraic curves

In this paper, we propose a method to explain mixed (i.e. continuous, discrete, ordinal, and categorical) de- pendent features by modeling the dependence structure of the features

Even in the case of fragments with a (probable) Norwegian medieval provenance, there is a question of how the books these fragments came from originally arrived in Norway: they

If this is done for all features in the feature set, using the observations in the dataset, then the features that most accurately split the data into text and shape stroke

We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include

Proposed algorithm employs Bag-of-Features (BoF) integration of a set of simple, 3D, local, geometrical features, so a 3D mod- el is described by an integrated feature vector per

• Given a set of point clouds of fragments of Terracotta, the method first extracts the feature lines on the original surfaces, and thereby the structured information is represented

Each observed feature is associated with a number of simulated features within a 50 km radius that are classified in three clusters using the K-Means multivariate clustering

The proposed method facilitates local merging of adjacent overlapping fragments along the z-direction while maintaining separated fragments far away from each other, capturing