2022
DOI: 10.1155/2022/7999312
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Deep Learning-Based 3D Shape Feature Extraction on Flash Animation Style

Abstract: Flash animation, as a kind of digital learning resource, is an important media for delivering information content, and more importantly, it is an important online learning resource with text, graphics, images, audio, video, interaction, dynamic effects, etc. Flash animation, with its powerful multimedia interaction and presentation capabilities, is widely used in distance education, high-quality course websites, Q&A platforms, etc. With the continuous development of deep learning, the 3D shape feature extr… Show more

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Cited by 2 publications
(3 citation statements)
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“…Zhu and Lee [26] have developed Using Flash animation style and deep learning, 3D shape feature extraction is done. Combining deep learning with conventional 3D shape feature extraction techniques can help to increase the precision of 3D shape data classification and retrieval tasks and alleviate the bottleneck of nondeep learning techniques, particularly for non-rigid 3D shapes.…”
Section: Literature Surveymentioning
confidence: 99%
See 1 more Smart Citation
“…Zhu and Lee [26] have developed Using Flash animation style and deep learning, 3D shape feature extraction is done. Combining deep learning with conventional 3D shape feature extraction techniques can help to increase the precision of 3D shape data classification and retrieval tasks and alleviate the bottleneck of nondeep learning techniques, particularly for non-rigid 3D shapes.…”
Section: Literature Surveymentioning
confidence: 99%
“…The amount of time that data takes to travel through a neural network is referred to as the end-to-end delay, encompassing both inference and any pre-processing or post-processing steps. In (26) the End to End Delay is computed.…”
Section: ) End To End Delaymentioning
confidence: 99%
“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”
mentioning
confidence: 99%