DSpace Repository

Predicting Tourist Spot by Using Machine Learning Approach

Show simple item record

dc.contributor.author Roy, Pranta
dc.contributor.author Yeasmin, Farjana
dc.contributor.author Binti, Most Afrin Nahar
dc.date.accessioned 2022-10-08T03:32:36Z
dc.date.available 2022-10-08T03:32:36Z
dc.date.issued 2022-01-04
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/8631
dc.description.abstract Tourism plays significant role for enhancing economic potential worldwide. The natural beauty and historical interests of Bangladesh remarked as a major tourist destination for the international tourists. In this study, we target to propose a Machine learning based application to recognize historical interests and tourist spots from an images. Making use of on-device Neural Engine comes with modern devices makes the application robust and internet free user experience. One of the difficult tasks to collect real images from tourist sites. Our collected images were in different sizes because of using different smartphones. We used following machine learning algorithms– Convolution Neural Network (CNN), Support Vector Machine (SVM), Long Short-Term Memory (LSTM), K-Nearest Neighbor (KNN) and Recurrent Neural Network (RNN). In this proposed framework, tourists can effortlessly detect their targeted places that can boost the tourism sector of Bangladesh. For this regard, Convolutional Neural Network (CNN) achieved best accuracy. en_US
dc.language.iso en_US en_US
dc.publisher Daffodil International University en_US
dc.subject Tourism en_US
dc.subject Economic stabilization en_US
dc.subject Machine learning en_US
dc.subject Tourist maps en_US
dc.title Predicting Tourist Spot by Using Machine Learning Approach 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