Recently, a novel signal-processing tool was proposed, the scattering transform, which uses
a cascade of wavelet filters and nonlinear (modulus) operations to build translation-invariant …

Visual analysis and authentication of artworks are challenging tasks central to art history and
criticism. This preliminary study presents a computational tool for scholars examining and …

This thesis addresses the problem of pattern and texture recognition from a mathematical
perspective. These high level tasks require signal representations enjoying specific …

A wavelet scattering network computes a translation invariant image representation which is
stable to deformations and preserves high-frequency information for classification. It …

In recent years, transformers, initially developed for language, have been successfully
applied to visual tasks. Vision transformers have been shown to push the state of the art in a …

This thesis is concerned with the problem of visual recognition in art–such as finding the
objects (eg cars, cows and cathedrals) present in a painting, or identifying the subject of an …

Art authentication is the process of identifying the artist who created a piece of artwork and is
manifested through events of provenance, such as art gallery exhibitions and financial …

The ever increasing availability of digital data from the Arts and cultural heritage calls for
efficient methods to organise, categorise, and retrieve such information in an effective and …

This paper presents a sparse representation based complete kernel marginal Fisher
analysis (SCMFA) framework for categorizing fine art images. First, we introduce several …

Deep learning techniques are increasingly used to automate categorization and
identification tasks for large datasets of digital photographs. For rasterized images formats …