This paper is published in Volume-6, Issue-1, 2020
Area
Electronics Engineering
Author
Swati Sorte, Dr. Prashant Sharma
Org/Univ
G. H. Raisoni College of Engineering, Nagpur, Maharashtra, India, India
Keywords
Level features, Detector performance, Multimedia applications, Video retrieval, Anomaly dataset
Citations
IEEE
Swati Sorte, Dr. Prashant Sharma. Video classification detection technique for spatial and temporal motion identification using pathway system, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Swati Sorte, Dr. Prashant Sharma (2020). Video classification detection technique for spatial and temporal motion identification using pathway system. International Journal of Advance Research, Ideas and Innovations in Technology, 6(1) www.IJARIIT.com.
MLA
Swati Sorte, Dr. Prashant Sharma. "Video classification detection technique for spatial and temporal motion identification using pathway system." International Journal of Advance Research, Ideas and Innovations in Technology 6.1 (2020). www.IJARIIT.com.
Swati Sorte, Dr. Prashant Sharma. Video classification detection technique for spatial and temporal motion identification using pathway system, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Swati Sorte, Dr. Prashant Sharma (2020). Video classification detection technique for spatial and temporal motion identification using pathway system. International Journal of Advance Research, Ideas and Innovations in Technology, 6(1) www.IJARIIT.com.
MLA
Swati Sorte, Dr. Prashant Sharma. "Video classification detection technique for spatial and temporal motion identification using pathway system." International Journal of Advance Research, Ideas and Innovations in Technology 6.1 (2020). www.IJARIIT.com.
Abstract
In Video classification, the Video scene or the tracking technology, which divides the Video into semantic sections, is an important element for adding insight and searching for metadata for Video. 5 Data augmentation is one of the main methods of addressing the problem of learning to take few shots, but current syntheses are only tackling the detection of crime scene per image when in reality images can contain several movements with respect to crime.
