Image Popularity Prediction
| Thesis title in Czech: | Předpovídání popularity obrázků |
|---|---|
| Thesis title in English: | Image Popularity Prediction |
| Key words: | {Deep Learning}|{Convolutional Neural Networks}|{Language models}|{Sentiment Analysis} |
| English key words: | {Deep Learning}|{Convolutional Neural Networks}|{Language models}|{Sentiment Analysis} |
| Academic year of topic announcement: | 2022/2023 |
| Thesis type: | diploma thesis |
| Thesis language: | angličtina |
| Department: | Department of Theoretical Computer Science and Mathematical Logic (32-KTIML) |
| Supervisor: | Mgr. Martin Pilát, Ph.D. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 30.05.2022 |
| Date of assignment: | 05.06.2022 |
| Confirmed by Study dept. on: | 09.06.2022 |
| Date and time of defence: | 05.09.2023 09:00 |
| Date of electronic submission: | 20.07.2023 |
| Date of proceeded defence: | 05.09.2023 |
| Opponents: | Mgr. Jan Hajič, Ph.D. |
| Guidelines |
| Machine learning has achieved great results in many image processing tasks, such as image classification and object detection. Recently, similar techniques have also been used to predict the popularity of images on social networks. The goal of this thesis is to study what affects the popularity of content on social networks and create models for predicting the popularity of images.
The student will study papers related to image processing and popularity prediction. He will also prepare a dataset of images together with an evaluation of their popularity. Based on this information, the student will create a model for predicting the popularity of images and compare it to existing models for this task. |
| References |
| [1] Zhang, Wei, Wen Wang, Jun Wang, and Hongyuan Zha. "User-guided hierarchical attention network for multi-modal social image popularity prediction." In Proceedings of the 2018 World Wide Web Conference, pp. 1277-1286. 2018. ACM. DOI: 10.1145/3178876.3186026
[2] Lin, Hung-Hsiang, Jiun-Da Lin, Jose Jaena Mari Ople, Jun-Cheng Chen, and Kai-Lung Hua. "Social Media Popularity Prediction Based on Multi-Modal Self-Attention Mechanisms." IEEE Access 10 (2021): 4448-4455. IEEE. DOI: 10.1109/ACCESS.2021.3136552 [3] Goodfellow I., Bengio Y., Courville, A.: "Deep Learning". MIT Press, 2016. ISBN: 978-0262035613. Online: http://www.deeplearningbook.org [4] Flach P.: "Machine Learning: The Art and Science of Algorithms that Make Sense of Data". Cambridge University Press, 2012. ISBN: 978-1107422223 |