• Neha Himesh
• Shriya R
• Gowthami PN
• Benish Roshan

Monument recognition is a challenging problem in the domain of image classification due to huge variations in the architecture of different monuments. Different orientations of the structure play an important role in the recognition of the monuments in their images. This paper proposes an approach for classification of various monuments using Convolutional Neural Network (CNN) Architecture using a GPU unit. The model is trained on representations of different Indian monuments, obtained from cropped images, which exhibit geographic and cultural diversity. Experiments have been carried out on the manually acquired dataset that is composed of 660 images of 10 different monuments where each monument has images from different angular views. The model was able to achieve accuracy above 90 percent for all the different monuments.

monument recognition;Convolutional Neural Networks; image classification

"Indian Monument Recognition using CNN Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.286-289, June-2019, Available :http://www.jetir.org/papers/JETIR1905N43.pdf

"Indian Monument Recognition using CNN Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp286-289, June-2019, Available at : http://www.jetir.org/papers/JETIR1905N43.pdf