Evidence map›Paper›PMID 35154310›Full record

ArticleComputational intelligence and neuroscience2022

Multimedia Character Modeling Design and Modeling of Cartoon Animation Based on Bayesian Sequence Recommendation Algorithm.

Hao Wu, Shi-Jiang Wen, Jong-Hoon Yang

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hao WuDepartment of Digital Image in Sangmyung University, Seoul 03015, Republic of Korea.ORCID https://orcid.org/0000-0002-1951-6651
Shi-Jiang WenDepartment of Digital Image in Sangmyung University, Seoul 03015, Republic of Korea.ORCID https://orcid.org/0000-0002-1519-1079
Jong-Hoon YangDepartment of Digital Image in Sangmyung University, Seoul 03015, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the continuous development of the social economy, cartoon animation and other multimedia and streaming media forms are becoming more and more popular and are loved by all kinds of people, such as monkey king and Nezha. However, the multimedia of these cartoon animation needs to conform to mainstream values and transmit positive energy. In view of these needs and shortcomings, this study relies on the Bayesian sequence recommendation algorithm, combs the three-tier architecture diagram of multimedia character modeling, analyzes it, respectively, from the perspectives of hierarchy, behavior, and interactive process, and tries to build corresponding animation design management documents, so as to provide corresponding decision-making basis to produce animation and develop corresponding results, provide corresponding reference mode for cartoon animation multimedia character manufacturing, complete corresponding cartoon animation multimedia characters faster, and improve cartoon animation multimedia works and efficiency. The simulation results show that the Bayesian sequence recommendation algorithm is effective and can support the design and modeling of cartoon animation multimedia characters.

Indexed as

AlgorithmsMultimediaBayes TheoremComputer Simulation

Identifiers

PMID35154310
PMCPMC8824738

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.