USING AI TO TRACE REGIONAL ART LINEAGES

Authors

  • Harsimrat Kandhari Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, Solan, 174103, India
  • Sanjivani Deokar Department of Computer Engineering, Lokmanya Tilak College of Engineering, Mumbai University, Maharashtra, India.
  • Pancham Cajla Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India
  • Swati Srivastava Associate Professor, School of Business Management, Noida international University 203201
  • Dr. Pooja Bhatt Assistant Professor, Department of Computer science and Engineering, Faculty of Engineering and Technology, Parul institute of Engineering and Technology, Parul University, Vadodara, Gujarat, India

DOI:

https://doi.org/10.29121/shodhkosh.v6.i2s.2025.6725

Keywords:

Artificial Intelligence, Art Lineage, Visual Semiotics, Neural Networks, Cultural Heritage, Regional Art History

Abstract [English]

The utilization of artificial intelligence (AI) in art-historical studies has revolutionary potential of understanding the way of how regional art traditions evolve and interrelate. In this paper, the advantages of applying computational approaches to tracing artistic traditions across time and culture are examined, especially through image recognition, neural networks and information-guided ontologies. The combination of art-historical concepts of descent, impact, and place-making with current visual semiotics, pattern recognition resulted in the creation of the framework that allows interpreting stylistic development in an algorithmic manner. The theoretical background highlights the essence of the digital methodologies that not only complement the traditional historiography, but also transform the paradigms of the interpretation of cultural heritage. The technological aspect of this work explores AI models, which can help detect visual repetitions, stylistic continuations, and regional differences in data collections on digital museums and art repositories. The aspects of creation and curation of training datasets are considered, along with ethical concerns of cultural bias in the algorithmic learning. The study plan comprises of case-studies of the chosen regional art genres in order to build an AI pipeline that visualizes the genealogies of style, providing an objective measure of the aesthetical impact and change. In conclusion, this paper has shown that AI can be used as a tool of analysis and curation, in order to promote the documentation, conservation and sharing of local art heritage. Its wider ramifications apply to the field of educational innovation, museum curation, and digital humanities, implying that algorithmic approaches can have a constructive impact on art historiography, helping to understand other cultures and explaining the way arts are happening in the world.

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Published

2025-12-16

How to Cite

Kandhari, H., Deokar, S., Cajla, P., Srivastava, S., & Bhatt, P. (2025). USING AI TO TRACE REGIONAL ART LINEAGES. ShodhKosh: Journal of Visual and Performing Arts, 6(2s), 491–500. https://doi.org/10.29121/shodhkosh.v6.i2s.2025.6725