Analysis and Importance of Deep Learning for Video Aesthetic Assessments

Authors(3) :-Manish Bendale, Madhura V. Phatak, Dr. Nitin N. Pise

Deep Learning is one of the active analysis topic obtaining a great deal of analysis attention recently. This increase in analysis interest is driven by several area as that are being worked on like machine-based reality finding, good over-seeing, sensory activity recognition, online learning, world of advertisement, text analysis and so on. Videos have specific characteristics that make their method unique. Visual aesthetic typically: Remember what they see, understand and learn rather than what they hear. This paper principally emphasizes deep learning on basics of automatic video aesthetic assessments.

Authors and Affiliations

Manish Bendale
Department of Computer Engineering, MIT, Pune, Maharashtra, India
Madhura V. Phatak
Department of Computer Engineering, MIT, Pune, Maharashtra, India
Dr. Nitin N. Pise
Department of Computer Engineering, MIT, Pune, Maharashtra, India

Video Aesthetics, Preprocessing Techniques, Feature Extraction, Deep Learning, Applications.

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Publication Details

Published in : Volume 5 | Issue 1 | January-February 2019
Date of Publication : 2019-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 546-554
Manuscript Number : CSEIT1951100
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Manish Bendale, Madhura V. Phatak, Dr. Nitin N. Pise, "Analysis and Importance of Deep Learning for Video Aesthetic Assessments", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 1, pp.546-554, January-February-2019. Available at doi :
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