Indian Monument Recognition Using Deep Learning

Abstract

Monuments are physical structures built or created dedicated to a person or event. Their importance to the region they belong to makes their documentation and preservation important. Monuments being 3D objects, pose is an issue in terms of the difference in perception of the monument images. There can be an immense variation because of the viewpoint from which the image is being taken. To overcome this issue, Data Augmentation is used in this study. Random Flip, Random Rotation, Random Translation and Random Zoom, Random Contrast, Random Hue, Random Brightness, and Random Saturation operations under Data Augmentation are applied on the dataset. This research uses Deep Learning architectures on a hybrid dataset of “Indian Monument Recognition Dataset” and “Qutub Complex Monuments' Images Dataset.” InceptionV3, MobileNet, ResNet50, AlexNet, and VGG16 recognize the monuments with an accuracy of 97.79%, 93.73%, 86.47%, 68.88%, and 61.33% respectively.

دراسة استطلاعية: التعرف على الآثار باستخدام الذكاء الاصطناعي

“…In [29] that same year, M. Trivedi emphasized that the postures of 3D object monuments are problematic. This issue is a result of divergent perceptions of the images of the monuments.…”