Blind Stereoscopic Image Quality Evaluator Based on Binocular Semantic and Quality Channels

Sim, Kyohoon; Yang, Jiachen; Lu, Wen; Gao, Xinbo

doi:10.1109/tmm.2021.3064240

Cited by 31 publications

(16 citation statements)

References 37 publications

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“…e future of wireless access networks will be a scenario of ultradense network deployment and the coexistence of multiple access technologies. Different types of IoT applications require matching connectivity to ensure service continuity [22][23][24][25][26][27][28]. However, the current network management architecture lacks the cooperation of convergence between different networks; for example, it is difficult to share information and resources between networks in real time.…”

Section: Machine Learning Algorithm Designmentioning

confidence: 99%

[Retracted] Machine Learning‐Based Offloading Strategy for Lightweight User Mobile Edge Computing Tasks

2021

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This paper presents an in-depth study and analysis of offloading strategies for lightweight user mobile edge computing tasks using a machine learning approach. Firstly, a scheme for multiuser frequency division multiplexing approach in mobile edge computing offloading is proposed, and a mixed-integer nonlinear optimization model for energy consumption minimization is developed. Then, based on the analysis of the concave-convex properties of this optimization model, this paper uses variable relaxation and nonconvex optimization theory to transform the problem into a convex optimization problem. Subsequently, two optimization algorithms are designed: for the relaxation optimization problem, an iterative optimization algorithm based on the Lagrange dual method is designed; based on the branch-and-bound integer programming method, the iterative optimization algorithm is used as the basic algorithm for each step of the operation, and a global optimization algorithm is designed for transmitting power allocation, computational offloading strategy, dynamic adjustment of local computing power, and receiving energy channel selection strategy. Finally, the simulation results verify that the scheduling strategy of the frequency division technique proposed in this paper has good energy consumption minimization performance in mobile edge computation offloading. Our model is highly efficient and has a high degree of accuracy. The anomaly detection method based on a decision tree combined with deep learning proposed in this paper, unlike traditional IoT attack detection methods, overcomes the drawbacks of rule-based security detection methods and enables them to adapt to both established and unknown hostile environments. Experimental results show that the attack detection system based on the model achieves good detection results in the detection of multiple attacks.

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Section: Machine Learning Algorithm Designmentioning

confidence: 99%

[Retracted] Machine Learning‐Based Offloading Strategy for Lightweight User Mobile Edge Computing Tasks

2021

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“…(2) e development of education helps to reduce the expenditure of natural resources and improve the efficiency of resource utilization. (3) Educational development contributes to the protection of natural resources and the environment [28,29]. rough education, people's awareness of environmental protection is raised, and people are encouraged to consciously participate in environmental protection activities and achieve sustainable economic development.…”

Section: E Effect Of Education On Economic Growthmentioning

confidence: 99%

[Retracted] Forecast and Evaluation of Educational Economic Contribution Based on Fuzzy Neural Network

Liu

2021

Complexity

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According to the theory that the degree of education of workers in educational economics has a certain positive relationship with social labor productivity, the fuzzy system and neural network modeling mechanism are used to establish the fuzziness of laborers’ education level to social productivity (per capita national income). This article combines fuzzy theory and neural network theory to construct an empirical model for the analysis of the contribution of education economy and conduct an empirical analysis of statistical data from 2010 to 2020. Analysis shows that there is a great correlation between per capita years of education and per capita GDP, especially the number of college students per million people has a greater correlation with per capita GDP. This fully confirms that economic growth is increasingly dependent on education, especially higher education. The main body of this article is the improvement of the measurement model and the calculation of the contribution of our country’s education to economic growth using the fuzzy neural network measurement model. The final empirical conclusion shows that education has a significant role in promoting the development of our country’s economy.

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“…e method based on the finite-dimensional linear model simplifies the spectral power distribution of the light source and the representation of object reflectivity, which is a big step forward in solving the problem of the insufficient constraint of color vision. It is one of the hot spots of illumination color compensation algorithms at present [31,32]. e existing light color compensation methods have their own limitations, and many problems are yet to be solved.…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Using Color Difference Compensation Method to Balance and Repair the Image of Art Design

Ji¹,

Shang

2021

Complexity

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In the case of complex illumination background, the image has fuzziness and chromatic aberration, which can improve the imaging effect of the image by white balance chromatic aberration compensation. The traditional method uses the contour feature fusion adaptive matching method to compensate the white balance under the complex illumination background, which leads to the good color difference compensation effect when the image pixel is low. A white balance color compensation algorithm for fuzzy chromatic aberration based on wavelet packet decomposition is proposed. The original image was denoised and filtered. The white balance characteristics of the image were analyzed and extracted based on the wavelet packet decomposition method, and the adaptive balance design was carried out to realize the white balance and color difference compensation of the art design chromatic aberration image. By using the known pixel information of the image block to be repaired, the statistical properties of the image block to be repaired are predicted, and the matching cost of the image block to be matched that meets the restriction conditions is calculated. By introducing the objective factor, the matching cost function is improved to balance the restoration process, and the unnatural problem caused by the repeated appearance of some image details in the restoration results is solved. The simulation results show that the method can effectively balance the color difference of the image, improve the aesthetic feeling of the image, and improve the performance of the detail features of the image. The peak signal-to-noise ratio is high.

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Blind Stereoscopic Image Quality Evaluator Based on Binocular Semantic and Quality Channels

Cited by 31 publications

References 37 publications

[Retracted] Machine Learning‐Based Offloading Strategy for Lightweight User Mobile Edge Computing Tasks

[Retracted] Machine Learning‐Based Offloading Strategy for Lightweight User Mobile Edge Computing Tasks

[Retracted] Forecast and Evaluation of Educational Economic Contribution Based on Fuzzy Neural Network

[Retracted] Using Color Difference Compensation Method to Balance and Repair the Image of Art Design

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