A Survey of Performance Optimization in Neural Network-Based Video Analytics Systems
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by
Nada Ibrahim, Preeti Maurya, Omid Jafari, Parth Nagarkar
2021
Abstract
Video analytics systems perform automatic events, movements, and actions
recognition in a video and make it possible to execute queries on the video. As
a result of a large number of video data that need to be processed, optimizing
the performance of video analytics systems has become an important research
topic. Neural networks are the state-of-the-art for performing video analytics
tasks such as video annotation and object detection. Prior survey papers
consider application-specific video analytics techniques that improve accuracy
of the results; however, in this survey paper, we provide a review of the
techniques that focus on optimizing the performance of Neural Network-Based
Video Analytics Systems.
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