The goal of this experimental thesis is to classify cinematographic shots by exploiting a convolutional neural network, also known as CNN. Usually CNNs are used to classify objects inside images, while in this case the CNN is used to classify images themselves using a partition similar to the frame partition typical of movie industry. The idea behind this project is to reduce the editing time of a video by classifying the video files. By doing so the video files will be divided according to the type of shot used. In this way during video editing it is known a priori where to look for a specific type of shots.