Abstract
First, the local feature extraction of the scale-invariant feature transformation algorithm, the classification excellence of the support vector machine, and the performance of the deep learning-based Fast-RCNN algorithm in the multi-scale feature extraction are analyzed and explained to design an intelligent background music system based on deep learning and Internet of Things (IoT) technology. Then, the intelligent background music system is applied to the Intelligent Home. On this basis, a feature extraction algorithm based on the middle-level feature structure is proposed, which extracts the underlying features of the scene images. Afterward, the critical functional components of the intelligent background music system are explained. Based on the actual operations, an intelligent background music system is designed based on deep learning and IoT. The results show that the recognition rate of indoor scenarios by the middle-level feature construction-based feature extraction algorithm is the highest, which is about 87.6%. The Gabor feature algorithm classifies and identifies the scenarios, and its recognition rate is always around 20%. In the bathroom, the recognition effect of the saliency map feature algorithm is similar to that of the middle-level feature construction-based feature extraction algorithm; however, in the bedroom, the recognition effect of the middle-level feature construction-based feature extraction algorithm is significantly better due to problems such as the lighting and room orientation. The effects of middle-level feature construction-based feature extraction algorithm on the classification and recognition of indoor scenarios are sound. In contrast, the proposed feature extraction algorithm based on deep learning has an optimal effect. The designed and implemented intelligent background music system is stable and effective, which provides a new idea and a new theoretical basis for the future research of intelligent background music system.
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Wen, X. Using deep learning approach and IoT architecture to build the intelligent music recommendation system. Soft Comput 25, 3087–3096 (2021). https://doi.org/10.1007/s00500-020-05364-y
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DOI: https://doi.org/10.1007/s00500-020-05364-y