Dynamically Selective Performance Optimization Method for Mobile 3D Graphics Application with N-Screen Service

Piao, Jin-Chun; Cho, Chang-Woo; Kim, Cheong-Ghil; Burgstaller, Bernd; Kim, Shin-Dug

doi:10.1007/s11277-015-3059-x

Cited by 2 publications

(1 citation statement)

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“…Piao et al described performance optimization methods for mobile graphics applications from two dimensions: graphics processing unit (GPU) performance and image quality. He provided an adaptive level of detail (LOD) configuration method for graphics applications through the OpenGL ES API level [4].…”

Section: Related Workmentioning

confidence: 99%

Optimization of Dynamic Graphic Packaging Design Scheme Based on Graph Neural Network

Tao

2022

Mobile Information Systems

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The traditional packaging design is inseparable from graphics, but the graphics is static, and the emergence of dynamic graphics breaks the conventional packaging design concept. This study optimized dynamic graph packaging design based on graph neural network technology. This paper first gives a brief introduction to the graph neural network, mainly to optimize the problem that the graph neural network has a large number of learning, and also expounds the principle of the graph neural network using formulas. Then this paper introduces the dynamic graphic packaging design in detail, which involves the elements of packaging design, the types of dynamic graphics, design ideas, and so on. Later, this paper tests users’ attention to the product through eye movement experiment and graph neural network algorithm. The experiment showed that the dynamic graphics packaging design of product 7 was the most popular, with the dynamic graphics area users viewed it up to 93 times. It can be seen that this dynamic graphic packaging design optimization scheme is effective, and it also provides a possibility for the optimization of dynamic graphic packaging design scheme.

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Section: Related Workmentioning

confidence: 99%