  Event detection is an important step in extracting knowledge from the video.
In this paper, we propose a deep learning approach to detect events in a soccer
match emphasizing the distinction between images of red and yellow cards and
the correct detection of the images of selected events from other images. This
method includes the following three modules: i) the variational autoencoder
(VAE) module to differentiate between soccer images and others image, ii) the
image classification module to classify the images of events, and iii) the
fine-grain image classification module to classify the images of red and yellow
cards. Additionally, a new dataset was introduced for soccer images
classification that is employed to train the networks mentioned in the paper.
In the final section, 10 UEFA Champions League matches are used to evaluate the
networks' performance and precision in detecting the events. The experiments
demonstrate that the proposed method achieves better performance than
state-of-the-art methods.
