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.