Research on the Construction of Intelligent Community Emergency Service Platform Based on Convolutional Neural Network

Chen, Yu; Tang, Zhong

doi:10.1155/2021/5089236

Cited by 17 publications

(5 citation statements)

References 29 publications

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“…The typical structure of CNN is shown in Figure 1 . Figure 1 is reproduced from the work of Chen and Tang (2021) [ 10 ] (under the Creative Commons (Attribution License/public domain)).…”

Section: Basic Theory Of Deep Learningmentioning

confidence: 99%

“…Figure 3 illustrates the convolution operation diagram. Figure 3 is reproduced from the work of Chen and Tang (2021) [ 10 ] (under the Creative Commons (Attribution License/public domain)). As can be seen from the figure, neurons at each adjacent level are compulsively connected with each other and have correlation relations.…”

Section: Basic Theory Of Deep Learningmentioning

confidence: 99%

“…Figure 4 is the pooling operation diagram. Figure 4 is reproduced from the work of Chen and Tang (2021) [ 10 ] [under the Creative Commons [Attribution License/public domain]]. In convolutional neural networks, pooling layer is often used to further adjust the output of the convolutional layer.…”

Section: Basic Theory Of Deep Learningmentioning

confidence: 99%

“…Figure 5 is the one-dimensional output obtained by convolution. Figure 5 is reproduced from the work of Chen and Tang [ 10 ] [under the Creative Commons [Attribution License/public domain]].…”

Section: Basic Theory Of Deep Learningmentioning

confidence: 99%

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Music Score Recognition Method Based on Deep Learning

Lin

2022

Computational Intelligence and Neuroscience

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In recent years, the recommendation application of artificial intelligence and deep music has gradually become a research hotspot. As a complex machine learning algorithm, deep learning can extract features with value laws through training samples. The rise of deep learning network will promote the development of artificial intelligence and also provide a new idea for music score recognition. In this paper, the improved deep learning algorithm is applied to the research of music score recognition. Based on the traditional neural network, the attention weight value improved convolutional neural network (CNN) and high execution efficiency deep belief network (DBN) are introduced to realize the feature extraction and intelligent recognition of music score. Taking the feature vector set extracted by CNN-DBN as input set, a feature learning algorithm based on CNN&DBN was established to extract music score. Experiments show that the proposed model in a variety of different types of polyphony music recognition showed more accurate recognition and good performance; the recognition rate of the improved algorithm applied to the soundtrack identification is as high as 98.4%, which is significantly better than those of other classic algorithms, proving that CNN&DBN can achieve better effect in music information retrieval. It provides data support for constructing knowledge graph in music field and indicates that deep learning has great research value in music retrieval field.

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“…The typical structure of CNN is shown in Figure 1 . Figure 1 is reproduced from the work of Chen and Tang (2021) [ 10 ] (under the Creative Commons (Attribution License/public domain)).…”

Section: Basic Theory Of Deep Learningmentioning

confidence: 99%

Section: Basic Theory Of Deep Learningmentioning

confidence: 99%

Section: Basic Theory Of Deep Learningmentioning

confidence: 99%

Section: Basic Theory Of Deep Learningmentioning

confidence: 99%

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Music Score Recognition Method Based on Deep Learning

Lin

2022

Computational Intelligence and Neuroscience

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“…With the rapid development of equestrian sports in China, it is urgent to strengthen the planning and management of equestrian venue complex construction. This paper puts forward an intelligent platform of equestrian venue complex based on intelligent sensor network, aiming at providing data support and decision-making basis for the development of equestrian industry in China [2][3].…”

Section: Introductionmentioning

confidence: 99%

Research on Intelligent Platform of Equestrian Complex Construction Based on Intelligent Sensor Network

Zhang,

Li,

Huang

2023

Atlantis Highlights in Engineering

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With the continuous improvement of people's living standards, equestrian sports have gradually entered people's field of vision. Equestrian sports, as a sport with great ornamental and competitive value, can not only provide high-quality sports services, but also create more employment opportunities for the city. This paper analyzes the present situation of equestrian venue complex construction in China. Aiming at the existing problems, an intelligent platform of equestrian venue complex is built based on intelligent sensor network, aiming at realizing data resource sharing, interconnection, remote management and big data analysis of equestrian venue complex, and providing data support and decision-making basis for equestrian venue complex construction.

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