Wavelet-content-adaptive BP neural network-based deinterlacing algorithm

Wang, Jin

doi:10.1007/s00500-017-2968-x

Cited by 11 publications

(7 citation statements)

References 10 publications

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“…Long-standing speculation has focused on the possibility of artificial intelligence, or so-called "intelligence," being utilised to perform tasks such as world interpretation and modification. All aspects of perception, including what we see, believe, and do, are intertwined with one another [4]. A person's intelligence is defined by their ability to learn new things, absorb new information, and put that learning to use in the real world.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Environmental Parameters of Ice and Snow Sports Venues Based on the BP Neural Network and Wireless Communication Technology

Yao

et al. 2022

Wireless Communications and Mobile Computing

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Ice and snow sports have become a scene of attraction nowadays. It not only encourages sports but also earns more revenue through tourism. Tourists love and admire this kind of sport because of its uniqueness, unlike other sports. The Olympic Games also conduct ice and snow sports under the Winter Olympic Sports. This kind of sport is played in ice rinks. Ice rinks are of two types, namely, natural and artificial. Natural ice rinks are formed in snowy regions, whereas artificial ice rinks can be set up anywhere with the help of technology. An artificial or natural ice rink, a sports venue, or a stadium is constructed accordingly. This research focuses on the optimization of environmental parameters of the ice and snow sports venue based on the BP neural network and wireless communication technology. There are various factors to be monitored when an indoor ice and snow sports venue is being considered. They are temperature monitoring, health monitoring of the audience, natural disaster detection and alarm in the case of natural ice rinks, and building safety concerning the climatic conditions. The proposed methodology uses BP neural networks and wireless communication technology to optimize the environmental parameters of the ice and snow sports venue. It has been demonstrated to have numerous advantages over traditional ice and snow sports methods. In this research, the convolutional BP neural network algorithm was implemented to analyse the environmental parameters of the chosen sport. The proposed algorithm is compared with the existing weighted centroid model. The results show that the proposed model has achieved an accuracy of 99.45%.

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Section: Introductionmentioning

confidence: 99%

Optimization of Environmental Parameters of Ice and Snow Sports Venues Based on the BP Neural Network and Wireless Communication Technology

Yao

et al. 2022

Wireless Communications and Mobile Computing

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show abstract

“…In recent years, the neural network model has been successfully applied to economic prediction. For this reason, we use the BP learning algorithm of an artificial neural network to study the prediction of sports achievement [5,6].…”

Section: Introductionmentioning

confidence: 99%

Research on Sports Performance Prediction Based on BP Neural Network

Yang

Luo

Tan

2021

Mobile Information Systems

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Artificial neural network has the advantages of self-training and fault tolerance, while BP neural network has simple learning algorithms and powerful learning capabilities. The BP neural network algorithm has been widely used in practice. This paper conducts research on sports performance prediction based on 5G and artificial neural network algorithms. This paper uses the BP neural network algorithm as a pretest modelling method to predict the results of the 30th Olympic Men’s 100m Track and Field Championships and is supported by the MATLAB neural network toolbox. According to the experimental results, the scheme proposed in this paper has better performance than the other prediction strategies. In order to explore the feasibility and application of the BP neural network in this kind of prediction, there is a lot of work to be done. The model has a high prediction accuracy and provides a new method for the prediction of sports performance. The results show that the BP neural network algorithm can be used to predict sports performance, with high prediction accuracy and strong generalization ability.

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“…In addition, BP was a common method of training artificial neural networks to minimize the objective function, which was a supervised learning method (Wang & Jeong, ). After network was decided, BP network studies and modifies the connecting weight and threshold value among neural units, according to the input and output of input example, to make network achieve presented mapping relation between input and output (Liu et al, ).…”

Section: Methodsmentioning

confidence: 99%

Study on pesticide residues classification of lettuce leaves based on polarization spectroscopy

Zhou

Sun

et al. 2018

J Food Process Engineering

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In order to effectively implement the rapid and nondestructive testing of pesticide residues in lettuce leaves, polarization spectral detection technology was used in this article. There were 90 pieces of lettuce leaves from five different groups, as well as a total of 450 samples of lettuce were used to collect polarization spectral information. CARS, IRIV, and SPA were used to obtain optimal wavelengths. BP neural network, KNN, and SVM were used to establish classification models. The results showed that the significance of these parameters from primary factor to secondary factor were incident zenith angle A, detector polarization angle D, detecting zenith angle B, and sample stage azimuth E, respectively. Besides, optimal level of A, B, D, and E were 60°, 45°, 30°, and 270°, respectively. Furthermore, the best classification model different kinds of pesticide residues in lettuce leaves was CARS‐SVM model, with calibration identification rate of 100%, prediction identification rate of 97.78%. It confirms that polarization spectral detection technology is a feasible and effective method for classifying different pesticide residues in lettuce leaves. Practical applications It is of great significance to understand the effects of pesticide residues on the biological structure and to reveal new biological functions and mechanisms of action. In order to effectively implement the rapid and nondestructive testing of pesticide residues in lettuce leaves, polarization spectral detection technology was used in this article. In addition, the order and superior level of polarization spectral factor were obtained through the calculation of the range using orthogonal test. It confirms that the polarization spectra is a feasible and effective method for discriminating different pesticide residues in lettuce leaves.

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Wavelet-content-adaptive BP neural network-based deinterlacing algorithm

Cited by 11 publications

References 10 publications

Optimization of Environmental Parameters of Ice and Snow Sports Venues Based on the BP Neural Network and Wireless Communication Technology

Optimization of Environmental Parameters of Ice and Snow Sports Venues Based on the BP Neural Network and Wireless Communication Technology

Research on Sports Performance Prediction Based on BP Neural Network

Study on pesticide residues classification of lettuce leaves based on polarization spectroscopy

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