AI-Based Image Classification for Indian Temple Iconography: A CNN-Based Approach

India is a country that encompasses a vast and diverse cultural and historical legacy, including numerous architecturally significant sculptures in temples. Analyzing and identifying entities in temple sculptures is a highly challenging and complex task. Digital archives with images, videos, books, interviews, and other resources can significantly accelerate iconographic research by building on past studies. This study explores image classification techniques applied to archives to enhance iconographic study. The findings contribute to the broader discourse on Indian art and culture, providing valuable insights into the intricate iconographic representations found in temple architecture.

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Publication Details

Published
2025-02-06
DOI
https://doi.org/10.1109/aide64228.2025.10987322
Citations
1
Primary Topic
Currency Recognition and Detection
Type
article
Field-Weighted Citation Impact
1.28
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article

AI-Based Image Classification for Indian Temple Iconography: A CNN-Based Approach

Aprna Tripathi, Lubna Ansari, Vijayalakshmi G. V. Mahesh
1 citations
Currency Recognition and Detection
1.28
article

AI-Based Image Classification for Indian Temple Iconography: A CNN-Based Approach

Aprna Tripathi, Lubna Ansari, Vijayalakshmi G. V. Mahesh
article en
1 citations

Abstract

India is a country that encompasses a vast and diverse cultural and historical legacy, including numerous architecturally significant sculptures in temples. Analyzing and identifying entities in temple sculptures is a highly challenging and complex task. Digital archives with images, videos, books, interviews, and other resources can significantly accelerate iconographic research by building on past studies. This study explores image classification techniques applied to archives to enhance iconographic study. The findings contribute to the broader discourse on Indian art and culture, providing valuable insights into the intricate iconographic representations found in temple architecture.

Mangalayatan University (IN), Manipal University Jaipur
Openalex Percentile: Top 20%
Currency Recognition and Detection
1.28
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