  Video content classification is an important research content in computer
vision, which is widely used in many fields, such as image and video retrieval,
computer vision. This paper presents a model that is a combination of
Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) which
develops, trains, and optimizes a deep learning network that can identify the
type of video content and classify them into categories such as "Animation,
Gaming, natural content, flat content, etc". To enhance the performance of the
model novel keyframe extraction method is included to classify only the
keyframes, thereby reducing the overall processing time without sacrificing any
significant performance.
