Classification of the Video Type and Device Used in 360-Degree Videos from the Trajectories of its Viewers’ Orientations with LSTM Neural Network Models
Author:
Affiliation:
1. Multimedia Information Technologies Laboratory (LTIM), Department of Mathematics and Computer Science, University of the Balearic Islands, Spain
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3505284.3532975
Reference11 articles.
1. Shooting a moving target: Motion-prediction-based transmission for 360-degree videos
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4. Felix A. Gers and Jurgen Schmidhuber. 2000. Recurrent nets that time and count . In Proceedings of the International Joint Conference on Neural Networks, 189–194 . https://doi.org/10.1109/ijcnn. 2000 .861302 10.1109/ijcnn.2000.861302 Felix A. Gers and Jurgen Schmidhuber. 2000. Recurrent nets that time and count. In Proceedings of the International Joint Conference on Neural Networks, 189–194. https://doi.org/10.1109/ijcnn.2000.861302
5. Learning to Forget: Continual Prediction with LSTM
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