References
Ramires A, Cocharro D, Davies M E P. An audio-only method for advertisement detection in broadcast television content. 2018, arXiv preprint arXiv:1811.02411
Luo C, Peng Y, Zhu T, Li L. An optimization framework of video advertising: using deep learning algorithm based on global image information. Cluster Computing, 2019, 22(4): 8939–8951
Hossari M, Dev S, Nicholson M, Mccabe K, Nautiyal A, Conran C, et al. ADNet: a deep network for detecting adverts. In: Proceedings of CEUR Workshop. 2018, 45–53
Qian X, Tang G. Research on TV advertisement detection base on video shot. In: Proceedings of the 3rd International Conference on System Science, Engineering Design and Manufacturing Informatization. 2012, 245–248
Zhang B, Xu B. Context-dependent audio-visual and temporal features fusion for TV commercial detection. In: Proceedings of International Symposium on Circuits and Systems. 2013, 5–8
Hannane R, Elboushaki A, Afdel K, Naghabhushan P, Javed M. An efficient method for video shot boundary detection and keyframe extraction using SIFT-point distribution histogram. International Journal of Multimedia Information Retrieval, 2016, 5(2): 89–104
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This work was supported and funded by the Directorate ASR&TD of UET-Taxila (UET/ASR&TD/RG-1002).
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Toheed, A., Javed, A., Irtaza, A. et al. An automated framework for advertisement detection and removal from sports videos using audio-visual cues. Front. Comput. Sci. 15, 152313 (2021). https://doi.org/10.1007/s11704-019-9187-9
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DOI: https://doi.org/10.1007/s11704-019-9187-9