# Object classification in images of Neoclassical furniture using Deep Learning

## TL;DR

This paper presents a deep learning-based framework for classifying objects in images of Neoclassical furniture to support cultural and aesthetic analysis.

## Contribution

It introduces a novel object recognition approach tailored for Neoclassical furniture images within a symbolic alignment context.

## Key findings

- Effective object classification achieved in furniture images
- Supports cultural transfer analysis of aesthetic forms
- Framework facilitates alignment with symbolic models

## Abstract

This short paper outlines research results on object classification in images of Neoclassical furniture. The motivation was to provide an object recognition framework which is able to support the alignment of furniture images with a symbolic level model. A data-driven bottom-up research routine in the Neoclassica research framework is the main use-case. It strives to deliver tools for analyzing the spread of aesthetic forms which are considered as a cultural transfer process.