Please use this identifier to cite or link to this item: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9965
Title: Landmark Classification using Deep Learning
Authors: Attri, Nishant
Sharma, Aman [Guided by]
Keywords: Artificial neural networks
Convolutional neural networks
K-nearest neighbour
Global positioning system
Issue Date: 2023
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: When we were looking at the diaries we kept as children, we would always try to identify all the places we had visited at least once during those early years. Despite this, we have no memory of their names. There is no doubt that Indians love to visit a variety of temples, but they often forget the names of the temples they have visited. In addition to that, it is also possible to experience a feeling of shyness when we are not even able to mention to our peers that we have also been there. We should never forget who built this monument. Due to this, Landmark Detection has become a powerful tool that helps us remember the names of these places in the future just so that we will be able to recognize them in the future. When it comes to Landmark Detection, it is the process of detecting pieces of artwork, buildings, and monuments that have been constructed by humans in an image by analysing the landmarks in that image. As a matter of fact, there is a visual symbol when it comes to buildings, which is known as a landmark, which is characterized by a distinctive visual form, which is not owned by other regions, and is very strong due to the fact that it has a characteristic that is unique.
Description: Enrollment No. 191512
URI: http://ir.juit.ac.in:8080/jspui/jspui/handle/123456789/9965
Appears in Collections:B.Tech. Project Reports

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