Shot category detection based on object detection using convolutional neural networks

Shot category detection is a method that extracts classified shots which comprised of several sequenced frames. These are based on object detection, which relates feature extraction of image processing. Shot category detection is helpful to utilize the neural network. Neural networks are widely generalized to our society. Artificial neural networks applied in many kinds of researches and developments, which provide convenient technologies for fundamental knowledge of deep learning. In terms of artificial neural networks, we introduce shot category detection based on object detection using convolutional neural networks (CNN). This paper also proves that CNN is efficient for supervised learning.