Pengenalan Trailer Film Melalui Machine Learning Dan Deep Learning Dengan Normalisasi Sequence
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Institusion
Institut Teknologi Telkom Purwokerto
Author
Yohanes, Anom Pratitis
Subject
T Technology (General)
Datestamp
2021-06-09 07:11:30
Abstract :
Watching a film on Youtube or in the cinema has become a natural thing for children, adolescents, adults and parents. Some adults invite their children to watch movies in theaters regardless of the category. Watching action, horror and romance films can each teach children to perform scenes of violence, murder and kissing. Based on these problems, a tool is needed to detect movie trailers using machine learning and deep learning methods. In this study, using 18 videos of people standing still, walking and running. The video will be split into 2,719 dataset images. Furthermore, the image dataset is trained using one of the deep learning methods, namely the Convolutional Neural Network algorithm to produce a dictionary that will be used to detect movie trailers. By using 51 action film trailers, horror and romance were converted into 4,2719 image datasets and trained using the Convolutional Neural Network algorithm to produce sequence values. Then the sequence value is tested using several Machine Learning methods, namely k-nearest neighbor, support vector machine, extra tree classifier, random forest classifier, adaboost classifier, and gradient boosting classifier to get an accuracy value as a faster comparison using machine learning methods or deep learning methods. The results of training the accuracy value of the film trailer dataset using machine learning and deep learning methods are 93% and 100%, respectively. The results of the accuracy value test using machine learning and deep learning methods were 46% and 100%, respectively. The application of the film trailer recognition system through machine learning and deep learning can help the public in detecting movie trailers with the right accuracy. Keywords : Augmentation, Deep Learning, Film Trailer Detection, Machine Learning
Watching a film on Youtube or in the cinema has become a natural thing for children, adolescents, adults and parents. Some adults invite their children to watch movies in theaters regardless of the category. Watching action, horror and romance films can each teach children to perform scenes of violence, murder and kissing. Based on these problems, a tool is needed to detect movie trailers using machine learning and deep learning methods. In this study, using 18 videos of people standing still, walking and running. The video will be split into 2,719 dataset images. Furthermore, the image dataset is trained using one of the deep learning methods, namely the Convolutional Neural Network algorithm to produce a dictionary that will be used to detect movie trailers. By using 51 action film trailers, horror and romance were converted into 4,2719 image datasets and trained using the Convolutional Neural Network algorithm to produce sequence values. Then the sequence value is tested using several Machine Learning methods, namely k-nearest neighbor, support vector machine, extra tree classifier, random forest classifier, adaboost classifier, and gradient boosting classifier to get an accuracy value as a faster comparison using machine learning methods or deep learning methods. The results of training the accuracy value of the film trailer dataset using machine learning and deep learning methods are 93% and 100%, respectively. The results of the accuracy value test using machine learning and deep learning methods were 46% and 100%, respectively. The application of the film trailer recognition system through machine learning and deep learning can help the public in detecting movie trailers with the right accuracy. Keywords : Augmentation, Deep Learning, Film Trailer Detection, Machine Learning
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