Formulaic language identification model based on GCN fusing associated information

Meng, Fanqi; Zheng, Yujie; Bao, Songbin; Wang, Jingdong; Yang, Shuaisong

doi:10.7717/peerj-cs.984

Cited by 28 publications

(10 citation statements)

References 23 publications

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“…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

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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.

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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

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“…After detecting the spatiotemporal interest point in the video, the descriptor should be used to describe the point or region. According to the unique complexity of video data, the descriptor should be robust to the changes in video background, clutter, scale, and direction [13][14][15][16][17][18][19][20][21]. e so-called structure means that there are fixed topological constraints between the joint positions of bones in each frame; for example, the head joint is only connected with the neck joint.…”

Section: Feature Extraction Of Arm Movement In Wushumentioning

confidence: 99%

Arm Movement Analysis Technology of Wushu Competition Image Based on Deep Learning

Zhang

Song

2022

Computational Intelligence and Neuroscience

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In order to improve the recognition accuracy of action poses for athletes in martial arts competitions, it is considered that a single frame pose does not have the temporal features required for sequential actions. Based on deep learning, this paper proposes an image arm movement analysis technology in martial arts competitions. The motion features of the arm are extracted from the bone sequence. Taking human bone motion information as temporal dynamic information, combined with RGB spatial features and depth map, the spatiotemporal features of arm motion data are formed. In this paper, we set up a slow frame rate channel and a fast frame rate channel to detect sequential motion of images. The deep learning model takes 16 frames from each video as samples. The softmax classifier is used to get the classification result of which action category the human action in the video belongs to. The test results show that the accuracy and recall rate of the arm motion analysis technology based on deep learning in martial arts competitions are 95.477% and 92.948%, respectively, with good motion analysis performance.

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“…e intelligent translation system function module adopts the SIP signal management technology of NGN core technology, which can identify the diversity of media and signal management and support different types of multimedia access, such as pictures, audio, video, and so on. e functional understanding of the translation system is divided into three levels [15]. ey are data hierarchy, logical hierarchy, and presentation hierarchy.…”

Section: Functional Modules Of Intelligent Translation Systemmentioning

confidence: 99%

Construction of German Machine Intelligent Translation System Based on Data Mining Algorithm

Liu

2022

International Transactions on Electrical Energy Systems

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The continuous expansion of the international market makes more people pay attention to learning different languages. As one of the most popular languages, German is favored by scholars. The use of intelligent translation systems to learn German has become the main way of learning. The increasing development of science and technology is accompanied by the emergence of a large number of new German words. The traditional German intelligent translation system has a slow update speed of words and cannot recognize new words, which seriously affects the accuracy of the translation. According to these questions, in this paper, the data mining algorithm is introduced into the German machine intelligent translation system. By evaluating the German machine intelligent translation system using a data mining algorithm in four aspects: translation speed, accuracy rate, recall rate, and user satisfaction, the evaluation results found that the translation speed of the system increased by 4.68%, the accuracy rate increased by 4.2, the recall rate has increased by 3.8%, and the user satisfaction score has increased by 0.825 points. The data mining algorithm can improve the German machine intelligent translation system and users’ interest in learning and promote German education.

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Formulaic language identification model based on GCN fusing associated information

Cited by 28 publications

References 23 publications

Intelligent Correction Method of Shooting Action Based on Computer Vision

Intelligent Correction Method of Shooting Action Based on Computer Vision

Arm Movement Analysis Technology of Wushu Competition Image Based on Deep Learning

Construction of German Machine Intelligent Translation System Based on Data Mining Algorithm

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