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Τίτλος: Classification of Instagram photos: Topic modelling vs transfer learning
Συγγραφείς: Tsapatsoulis, Nicolas 
Major Field of Science: Social Sciences
Field Category: Media and Communications
Λέξεις-κλειδιά: image classification;transfer learning;topic modelling;deep learning
Ημερομηνία Έκδοσης: 7-Σεπ-2022
Πηγή: SETN '22: Proceedings of the 12th Hellenic Conference on Artificial Intelligence, 7 - 9 September 2022, Corfu, Greece, pp 1–7
Start page: 1
End page: 7
Περίληψη: The existence of pre-trained deep learning models for image classification, such as those trained on the well-known Resnet-50 architecture, allows for easy application of transfer learning to several domains including image retrieval. Recently, we proposed topic modelling for the retrieval of Instagram photos based on the associated hashtags. In this paper we compare content-based image classification, based on transfer learning, with the classification based on topic modelling of Instagram hashtags for a set of 24 different concepts. The comparison was performed on a set of 1944 Instagram photos, 81 per concept. Despite the excellent performance of the pre-trained deep learning models, it appears that text-based retrieval, as performed by the topic models of Instagram hashtags, stills perform better.
URI: https://hdl.handle.net/20.500.14279/29495
ISBN: 9781450395977
DOI: 10.1145/3549737.3549759
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Conference Papers
Affiliation: Cyprus University of Technology 
Εμφανίζεται στις συλλογές:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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