Autonomous Malicious Video Content Categorization Using Convolutional Neural Networks

Autonomous Video Content Categorization, as the name indicates, describes a technique where the input content gets reviewed automatically. Here, categorization means that given a video as an input to the system, the system classifies if it contains nudity content, gambling or alcoholic content. With the increasing volumes of data, bad video content review is becoming an important component in every field. Considerable time and effort get consumed in performing the manual content review, also the process of the creative display is delayed to the user. Here Convolutional Neural Network i.e. a class of deep neural network is used which consists of an input and an output layer, as well as multiple hidden layers. Deep learning is one such field which can give good results in that respect. Feature extractors like Convolutional neural networks (CNN) have proved to be significant in the field of video classification.