INDIAN MONUMENTAL IMAGE CLASSIFICATION USING DEEP LEARNING TECHNIQUES

The purpose of artificial intelligence (AI) is to construct machines that behave and function similarly to humans.The deep learning models are utilized for classification of Indian monumental images. This allows for the rapidand efficient classification of monumental images. Monumental classification is considered as a complicatedtask due to the angle and perspective variations, lighting conditions, architectural similarities and occlusions.For the proposed study, the Indian Heritage Image Retrieval Dataset (IHIRD) is used. The study had employeddeep learning methods like CNN, VGG16 and Resnet50 for efficient classification of monumental images. Toevaluate the model’s performance, the different metrics such as precision, recall, F1 score and validationaccuracy are adopted. As a result of exploring various models, it has been concluded that using the IHIRDdataset, the Resnet50 model had achieved accuracy of 94.20%, a precision of 95, a recall of 94 and f1score of94. It has been understood that the proposed model Resnet50 has performed well, and efficient for classificationand prediction for a variety of images when compared it to the other models