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RETRACTED ARTICLE: Human behaviour recognition and monitoring based on deep convolutional neural networks

Author

Listed:
  • Kechao Wang
  • Tiantian Wang
  • Lin Liu
  • Chengjun Yuan

Abstract

We, the Editors and Publisher of the journal Behaviour & Information Technology, have retracted the following article which was part of the Special Issue on Behaviour Monitoring and Management of Customers, People and Organizations using Deep Learning:Kechao Wang, Tiantian Wang, Lin Liu & Chengjun Yuan (2019) Human behaviour recognition and monitoring based on deep convolutional neural networks, Behaviour & Information Technology, DOI: 10.1080/0144929X.2019.1702101After publication it came to our attention that the person named as the Guest Editor of the Special Issue was impersonated by a fraudulent entity and the articles were not reviewed fully in line with the journal’s peer review standards and policy. We did not find any evidence of misconduct by the authors. However, in order to ensure full assessment has been conducted, we sought expert advice on the validity and quality of the published articles from independent peer reviewers. Following this post publication peer review, the editor has determined that the articles do not meet the required scholarly standards to remain published in the journal, and therefore has taken the decision to retract the articles. The authors have been informed of this decision.We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.The retracted articles will remain online to maintain the scholarly record, but they will be digitally watermarked on each page as ‘Retracted’.

Suggested Citation

  • Kechao Wang & Tiantian Wang & Lin Liu & Chengjun Yuan, 2021. "RETRACTED ARTICLE: Human behaviour recognition and monitoring based on deep convolutional neural networks," Behaviour and Information Technology, Taylor & Francis Journals, vol. 40(9), pages 1-1, July.
  • Handle: RePEc:taf:tbitxx:v:40:y:2021:i:9:p:xxx-xli
    DOI: 10.1080/0144929X.2019.1702101
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