DSpace Repository

A Model for Identifying Historical Landmarks of Bangladesh from Image Content Using a Depth-Wise Convolutional Neural Network

Show simple item record

dc.contributor.author Jeny, Afsana Ahsan
dc.contributor.author Junayed, Masum Shah
dc.contributor.author Atik, Syeda Tanjila
dc.contributor.author Mahamd, Sazzad
dc.date.accessioned 2021-11-30T07:53:42Z
dc.date.available 2021-11-30T07:53:42Z
dc.date.issued 2019-04-12
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6522
dc.description.abstract At present, tourism is considered to be one of the key factors shaping the development of a country’s economy. Most of the tourists tend to explore places that they find fascinating after watching pictures of that places over Internet. Anyone can know about a famous place by simply typing the name of that place in an internet browser. But problem arises when he/she comes across the image of a beautiful landmark which is anonymous as most of the time web images do not convey any text caption. Most of models provided for image identification so far exhibit much complex structure and increased time complexity. In this paper, we have proposed a CNN model based on MobileNet and TensorFlow for detecting some historical landmarks of Bangladesh from their image. We have examined 750 images from five different places and comparing other state-of-art models, our model holds relatively simpler structure and has achieved a significantly higher average accuracy of 99.2%. This model can be further enhanced to facilitate image classification in other related areas. en_US
dc.language.iso en_US en_US
dc.publisher Springer en_US
dc.subject Convolutional neural networks en_US
dc.subject Tensor Flow en_US
dc.subject Mobile Net en_US
dc.subject Historical place detection en_US
dc.subject Image processing en_US
dc.title A Model for Identifying Historical Landmarks of Bangladesh from Image Content Using a Depth-Wise Convolutional Neural Network en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Browse

My Account

Statistics