Study on Pixel Entanglement Theory for Imagery Classification

Zhou, Guoqing; Yang, Fan; Xiao, Jun Jun

doi:10.1109/tgrs.2022.3167569

Cited by 20 publications

(12 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The feedback and enhancement of proprioceptive information can be strengthened by means of assistance (i.e., hand handle) to help lift the elbow and arm, resistance (i.e., holding the elbow joint with a hand) to remind him not to abduct too much, and repeated unarmed imitation exercises, so as to improve the coordination of his whole body force [ 20 ]. Through the feedback of multichannel sensory information, promote the further improvement of differentiation inhibition, correct wrong movements, and successfully master the complete one-handed shoulder shooting skills [ 4 , 21 – 25 ].…”

Section: Intelligent Correction Methods Of Shooting Actionmentioning

confidence: 99%

See 1 more Smart Citation

Intelligent Correction Method of Shooting Action Based on Computer Vision

Wang

Feng³

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Aiming at the problem that the students’ long-term use of nonstandard shooting action leads to poor basketball teaching effect, an intelligent correction method of shooting action based on computer vision is proposed. Combined with the principle of computer vision, the image acquisition model of basketball shooting action is constructed. The edge contour and adaptive feature segmentation of basketball images are detected, and abnormal shooting movements are recognized. The intelligent correction model of shooting action is constructed, and the intelligent correction of shooting action is realized. Finally, through experiments, it is proved that the visual analysis and intelligent correction effect of basketball shooting action are obviously better, and it can correct shooting action in real time and accurately.

show abstract

Section: Intelligent Correction Methods Of Shooting Actionmentioning

confidence: 99%

“…rough the feedback of multichannel sensory information, promote the further improvement of differentiation inhibition, correct wrong movements, and successfully master the complete onehanded shoulder shooting skills [4,[21][22][23][24][25].…”

Section: Intelligent Correction Methods Of Shooting Actionmentioning

confidence: 99%

Intelligent Correction Method of Shooting Action Based on Computer Vision

Wang

Feng³

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…The greater the unevenness, the more uneven the force on the slope is, and the greater the possibility of geological disasters (Chen and Li, 2020). Theoretically, ground collapse density plays an important role in the occurrence of geological disasters (Hait and Head-Gordon, 2020;Zhang et al, 2022b;Zhou et al, 2022). The ground collapse significantly affects the surface stability of the mining area.…”

Section: Analysis Of Model Buildingmentioning

confidence: 99%

Sensitivity study of multi-field information maps of typical landslides in mining areas based on transfer learning

et al. 2023

View full text Add to dashboard Cite

The main purpose of this study is to analyze the main influencing factors of the landslide in the coal mine area and, on this basis, establish the sensitivity zoning model of the landslide. Considering the difficulty to obtain the expected results by using machine learning under the condition of lacking data, the typical landslide is used as the data basis, that is, the Fenxi coal mine and Xishan Bujiu coal mine are selected as the coal mining landslide points. Various factors, such as goaf, land subsidence, slope structure, formation lithology, and various indicators are used as input data sources, and artificial neural network (ANN) datasets are used for training to establish a pre-training model. Using the pre-training model, the mining landslide sensitivity evaluation model based on transfer learning is established. In order to demonstrate the performance of transfer learning more intuitively, the neural network is introduced to evaluate the evaluation model. The test results show that transfer learning can achieve a transfer effect higher than 0.95, and the regional distributions of highest landslide sensitivity calculated based on self-transfer learning, direct push transfer learning, and inductive transfer learning are 31.33, 35.50, and 33.75%, respectively, which further deduced that inductive transfer learning can be used for evaluating an LSP model.

show abstract

“…e more common features of smart factories include collaboration between machines and humans, self-learning capabilities of factory handling robots, visualization of the entire factory process, and self-healing capabilities [31][32][33]. Self-healing capability represents the ability of a factory to achieve self-healing of production lines in extreme weather or other catastrophic environments.…”

Section: Smart Factorymentioning

confidence: 99%

Application of Internet of Things in Smart Factories under the Background of Industry 4.0 and 5G Communication Technology

Diao

Sun

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

The key identification element of the smart factory is the interconnection between devices, which solves the production method and development dilemma of the factory under Industry 3.0 and previous models. The new article published by Xinhua News Agency on January 16, 2022, advocates the idea of industry+ Internet, and its main goal is to realize intelligent production. At present, smart factories have become the main development direction of industrial enterprises in the world. 5G technology has been rapidly deployed with the development of mobile communication, and its performance has also been greatly improved compared to previous communication technologies. After China put forward the smart manufacturing 2025 plan, although a large number of enterprises are still lingering in the process of research, learning, and exploration, the idea of Industry 4.0 has taken root in various intelligent manufacturing enterprises, and the development route of Chinese manufacturing enterprises in the future has been ahead of schedule. Direction. Based on the basic theory of Industry 4.0, 5G wireless communication, Internet of Things, and smart factories, this paper firstly distributed questionnaires to 20 enterprises with smart factories by means of network and interview and reanalyzed the collected questionnaires by regression analysis method and then used the questionnaire scale analysis method to analyze the reliability and validity of the questionnaire and combined with the results of the questionnaire analysis to analyze the problems existing in the current smart factory. Finally, based on the background of Industry 4.0 and 5G communication technology, combined with the Internet of Things technology, the development layout of the smart factory is designed; that is, based on the elliptic curve encryption algorithm, the signature mechanism of mutual trust of all electronic devices in the IoT smart factory is set to improve the smart factory.

show abstract

Study on Pixel Entanglement Theory for Imagery Classification

Cited by 20 publications

References 36 publications

Intelligent Correction Method of Shooting Action Based on Computer Vision

Intelligent Correction Method of Shooting Action Based on Computer Vision

Sensitivity study of multi-field information maps of typical landslides in mining areas based on transfer learning

Application of Internet of Things in Smart Factories under the Background of Industry 4.0 and 5G Communication Technology

Contact Info

Product

Resources

About