ArticleComputational intelligence and neuroscience2022
Comparative Analysis of Dynamic Characteristics between Electronic Signature and Conventional Signature Based on Computer Vision Technology.
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. It has been retracted, and should not be counted. Cited by 1 paper.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Retracted: Comparative Analysis of Dynamic Characteristics between Electronic Signature and Conventional Signature Based on Computer Vision Technology.Computational intelligence and neuroscience · 2023Article
Corrections and comments
- Retraction · 2023-12-13Compromised Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During the last two or three decades where innovations in technology have been dominant, especially the rapid development of electronic information technology, various types of electronic devices have been developed for different application areas. It is this technological-assisted equipment that has drastic effects on the lifestyle of every creature in general and human beings in particular. In addition to the other activities or services, technology has enabled human beings to write on electronic devices, which is due to the fact that these devices will generate electronic signature handwriting that is extremely useful for human beings. They may effectively cope with the electronization of traditional signature handwriting and ease the difficulties of authenticating the identification information of the signatory of electronic documents when used in conjunction with electronic documents. This method is frequently utilized in e-government, e-commerce, banking and insurance, medical care, and other industries. This study uses the current mainstream computer vision technology to compare and analyze the handwriting dynamic characteristics of electronic signature and conventional signature. It uses the electronic signature God and software to collect and extract the original characteristic data of user's electronic signature and then extracts the characteristics of average writing speed, duration, and average pressure on the basis of these data for analysis. Among these techniques, the writing time of electronic signature is longer than that of conventional signature, and the average speed of conventional signature notes is higher than that of electronic signature, and when analyzing the average pressure characteristics, the conventional signature pressure is greater than the electronic signature pressure.
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Registered trials
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.