Machine Learning Advances aiding Recognition and Classification of Indian Monuments and Landmarks
Aditya Jyoti Paul, Smaranjit Ghose, Kanishka Aggarwal, Niketha, Nethaji, Shivam Pal, Arnab Dutta Purkayastha

TL;DR
This paper surveys machine learning methods used for recognizing and classifying Indian monuments and landmarks, aiming to modernize tourism by providing automated, accurate, and engaging heritage information systems.
Contribution
It reviews recent research on machine learning techniques applied to monument recognition, highlighting progress and challenges in developing automated heritage information systems.
Findings
Machine learning improves monument recognition accuracy.
Automated systems can enhance tourist experience.
Research highlights key challenges and future directions.
Abstract
Tourism in India plays a quintessential role in the country's economy with an estimated 9.2% GDP share for the year 2018. With a yearly growth rate of 6.2%, the industry holds a huge potential for being the primary driver of the economy as observed in the nations of the Middle East like the United Arab Emirates. The historical and cultural diversity exhibited throughout the geography of the nation is a unique spectacle for people around the world and therefore serves to attract tourists in tens of millions in number every year. Traditionally, tour guides or academic professionals who study these heritage monuments were responsible for providing information to the visitors regarding their architectural and historical significance. However, unfortunately this system has several caveats when considered on a large scale such as unavailability of sufficient trained people, lack of accurate…
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