Predicting Episodic Video Memorability using Deep Features Fusion Strategy-Reference-Cited by-同舟云学术

Predicting Episodic Video Memorability using Deep Features Fusion Strategy

Published:2022-05-25 Issue: Volume: Page:
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Container-title:2022 IEEE/ACIS 20th International Conference on Software Engineering Research, Management and Applications (SERA)
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Author:

Ali Hasnain¹,Gilani Syed Omer²^ORCID,Khan Muhammad Jawad¹,Waris Asim²^ORCID,Khattak Muazzam Khan³,Jamil Mohsin⁴^ORCID

Affiliation:

1. National University of Sciences & Technology, NUST,Robotics & AI,Islamabad,Pakistan

2. National University of Sciences & Technology, NUST,Biomedical Engg & Sci,Islamabad,Pakistan

3. Computing Quaid-e-Azam University,Islamabad,Pakistan

4. Memorial University of Newfoundland,Electrical & Computer Engg,St. John's,NL,Canada

Publisher

IEEE

Link

Reference29 articles.

2. RUC at MediaEval 2018: Visual and Textual Features Exploration for Predicting Media Memorability;wang;MediaEval,2018

4. Predicting Media Mem-orability Using Deep Features with Attention and Recurrent Network;tran;MediaEval,2019

5. Densely connected convolutional networks;huang;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2017

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