Micromagnetic Analysis of Edge Effects in a Thin Magnetic Film during Local Excitation of Magnetization Oscillations

Belyaev, B. A.; Izotov, A. V.; Skomorokhov, G. V.; Solovev, P.N.

doi:10.1007/s11182-020-02106-3

Cited by 4 publications

(1 citation statement)

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“…The pictures' movements and the images' modeling are significant characteristics of the films. Films can be more attractive through excellent picture movements and image modeling (Belyaev et al, 2020 ). A film is an art form subject to mass media, and its visual appreciation can satisfy and comfort the audiences (Matbouly, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

The Use of Deep Learning and VR Technology in Film and Television Production From the Perspective of Audience Psychology

Tong

Cao²,

Sun

et al. 2021

Front. Psychol.

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As the development of artificial intelligence (AI) technology, the deep-learning (DL)-based Virtual Reality (VR) technology, and DL technology are applied in human-computer interaction (HCI), and their impacts on modern film and TV works production and audience psychology are analyzed. In film and TV production, audiences have a higher demand for the verisimilitude and immersion of the works, especially in film production. Based on this, a 2D image recognition system for human body motions and a 3D recognition system for human body motions based on the convolutional neural network (CNN) algorithm of DL are proposed, and an analysis framework is established. The proposed systems are simulated on practical and professional datasets, respectively. The results show that the algorithm's computing performance in 2D image recognition is 7–9 times higher than that of the Open Pose method. It runs at 44.3 ms in 3D motion recognition, significantly lower than the Open Pose method's 794.5 and 138.7 ms. Although the detection accuracy has dropped by 2.4%, it is more efficient and convenient without limitations of scenarios in practical applications. The AI-based VR and DL enriches and expands the role and application of computer graphics in film and TV production using HCI technology theoretically and practically.

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Section: Introductionmentioning

confidence: 99%