Scopus Indexed Publications

Paper Details


Title
Tourist Spot Recognition Using Machine Learning Algorithms
Author
Pranta Roy, Farjana Yeasmin Koly, Jahanggir Hossain Setu, Most. Afrin Nahar Binti, Nusrat Jahan,
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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 deep 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 is to collect real images from tourist sites. Our collected images were in different sizes because of using different smartphones. We used following deep 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 of 97%.

Keywords
"Tourism Deep learning Convolutional neural network Recurrent neural network Tourist spot"
Journal or Conference Name
Lecture Notes on Data Engineering and Communications Technologies
Publication Year
2023
Indexing
scopus