Using deep learning approach and IoT architecture to build the intelligent music recommendation system
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METHODOLOGIES AND APPLICATION
Using deep learning approach and IoT architecture to build the intelligent music recommendation system Xinglin Wen1
Springer-Verlag GmbH Germany, part of Springer Nature 2020
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 constructionbased 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. Keywords Artificial intelligence Internet of Things Intelligent Internet of Things Music system Deep learning
1 Introduction In recent years, the continuous development of science and technology has provided great convenience for the daily lives of people. As the embedded technology advances, intellectualizing software, network, control, and communication technologies has been possible in modern lives (Gu and Qiu 2018). The Internet of Things (IoT) refers to the interconnected network between objects and objects. It allows all everyday
Communicated by V. Loia. & Xinglin Wen [email protected] 1
Luxun School of the Arts, Yan’an University, Yan’an 716000, China
physical objects that can be independently addressed to form an interconnected network. It uses QR codes and bar codes to sto
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