ITM Web Conf.
Volume 40, 2021International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|Number of page(s)||6|
|Published online||09 August 2021|
Movie Posters’ Classification into Multiple Genres
Ramrao Adik Institute of Technology Nerul, Navi Mumbai
Our project intends to classify movies into the three most probable genres that they belong to, from a predefined set of 25 genres, based on only one image i.e the movie poster. We have made use of Convolutional Neural Networks (CNN) to realize this project as we believe it would be of help to extract the features and visual information from the image. Instead of a multi-class classification problem in which the input is classified into any one class, this project would be more correctly described as a multilabel classification problem as a movie belongs to more than one genre. In this project we see a comparative study of different architectures and tune them to yield the best result based on the metric of accuracy. We have applied various techniques such as data augmentation and L2 regularization to comparatively deduce the model that performs best from all the tested models.
© The Authors, published by EDP Sciences, 2021
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