Abstract
Geotagging is a rapidly growing technology in digital photography and searching for specific landmarks, and helps everyone in our daily lives. Navigation applications and travel guides put a number of geotagged photos on the maps, providing a good overview of the destination. Recently, the development of photo geotagging methods has become a popular issue. Implementations of the SIFT and SURF algorithms and training of convolutional neural networks to obtain image classification for landmark images are presented in this paper. Based on the results of the classification of images and geotags of other similar images, geotags have been assigned to the target images. In addition, the results of image classification obtained using feature detection algorithms and neural networks were compared and analyzed.
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Mu, S., Piwowarczyk, M., Kutrzyński, M., Trawiński, B., Telec, Z. (2020). Comparative Analysis of Selected Geotagging Methods. In: Sitek, P., Pietranik, M., Krótkiewicz, M., Srinilta, C. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Communications in Computer and Information Science, vol 1178. Springer, Singapore. https://doi.org/10.1007/978-981-15-3380-8_29
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