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 information, failure to convey the richness of details in an attractive format etc. Recently, machine learning approaches revolving around the usage of monument pictures have been shown to be useful for rudimentary analysis of heritage sights. This paper serves as a survey of the research endeavors undertaken in this direction which would eventually provide insights for building an automated decision system that could be utilized to make the experience of tourism in India more modernized for visitors.

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机器学习的进步有助于印度古迹和地标的识别和分类

印度的旅游业在该国经济中发挥着典型的作用，2018 年估计占 GDP 的 9.2%。 年增长率为 6.2%，该行业具有成为经济主要驱动力的巨大潜力。阿拉伯联合酋长国等中东国家。整个国家地理上展示的历史和文化多样性是世界各地人民的独特景观，因此每年吸引数以千万计的游客。传统上，研究这些古迹的导游或学术专业人士负责向游客提供有关其建筑和历史意义的信息。然而，不幸的是，这个系统在大规模考虑时有几个警告，例如没有足够的训练有素的人，缺乏准确的信息，未能以有吸引力的格式传达丰富的细节等。 最近，机器学习方法围绕纪念碑图片的使用已被证明可用于对遗产景点进行基本分析。本文对在这个方向上进行的研究工作进行了调查，最终将为构建自动化决策系统提供见解，该系统可用于使印度的旅游体验更加现代化。围绕纪念碑图片使用的机器学习方法已被证明对遗产景点的基本分析很有用。本文对在这个方向上进行的研究工作进行了调查，最终将为构建自动化决策系统提供见解，该系统可用于使印度的旅游体验更加现代化。围绕纪念碑图片使用的机器学习方法已被证明对遗产景点的基本分析很有用。本文对在这个方向上进行的研究工作进行了调查，最终将为构建自动化决策系统提供见解，该系统可用于使印度的旅游体验更加现代化。