  Analysis of respiratory sounds increases its importance every day. Many
different methods are available in the analysis, and new techniques are
continuing to be developed to further improve these methods. Features are
extracted from audio signals and trained using different machine learning
techniques. The use of deep learning, which is a different method and has
increased in recent years, also shows its influence in this field. Deep
learning techniques applied to the image of audio signals give good results and
continue to be developed. In this study, image filters were applied to the
values obtained from audio signals and the results of the features formed from
this were examined in machine learning and deep learning techniques. Their
results were compared with the results of methods that had previously achieved
good results.
