Convolutional Neural Networks and Thrir Classification for Large Scale Videos
Charu Jain, Aarti Chugh, Nisha Charaya · International Journal of Research in Advent Technology · 2019
The problems of image recognitions require powerful model implementation like convolutional neural networks (CNN).The obtained results based on extensive evaluation and classification of huge videos obtained from YouTube having more than one million views are used in this paper analysis.The CNN connectivity for additional advantages of temporary information in specific time domain is performed and architecture for multiple resolutions is shown as the result of classification of neural network.The significant improvement in performance from 50.3% to 65.3% shows the display significance for the neural network.But for case when model based on single frame is implemented, this improvement is very low [59% to 60%], but this little improvement is showing its significance.The performance generalization based on selected model and actions of UCF-101 is further studied in our paper.The base line of UCF-101 [44%] is considered as the measuring tool of improvement for reorganization and comparison of large scale videos.The classification is easily done with CNN.