Classification of Actors in an Animated Video using a Novel Yolo Framework in Comparison with SVM Algorithm
DOI:
https://doi.org/10.47750/pnr.2022.13.S04.187Keywords:
Deep Learning, Face detection, Image Classification, Novel You Only Look Once (YOLO) framework, Supervised Learning, Support vector machine.Abstract
Aim: The major goal of this study is Classification of actors in an animated video using the novel YOLO (You Only Look Once) framework in comparison with the SVM (Support Vector Machine) algorithm. Materials and Methods: Sample groups that are considered in the project can be classified into two, one for YOLO and other for SVM, which are tested using 0.80 for G-power to determine the sample size and for t-test analysis.Results and Discussion:- The analysis of results show that the You Only Look Once has a high accuracy (87.45%) in comparison with the Support Vector Machine (84.74%).The statistical significance difference (two-tailed) is
0.001 (p<0.05).Conclusion: Novel YOLO framework seems to be better in classification of actors in an animated video over the SVM algorithm.
