Object classification in images of Neoclassical furniture using Deep Learning
This provides a domain-specific tool for cultural heritage analysis, but it is incremental as it applies existing deep learning methods to a new dataset.
The paper tackled object classification in images of Neoclassical furniture using deep learning to support aligning images with symbolic models, resulting in a framework for analyzing aesthetic forms as cultural transfer processes.
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.