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RETRACTED ARTICLE: A Robust Face Emotion Recognition Approach through Optimized SIFT Features and Adaptive Deep Belief Neural Network
We, the Editor and Publisher of Journal of Applied Security Research, have retracted the following article: Yenumaladoddi Jayasimha & R. Venkata Siva Reddy, A Robust Face Emotion Recognition Approach through Optimized SIFT Features and Adaptive Deep Belief Neural Network, Journal of Applied Secu...
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Published in: | Journal of applied security research 2021-07, Vol.16 (3), p.I-XXII |
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Main Authors: | , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | We, the Editor and Publisher of Journal of Applied Security Research, have retracted the following article:
Yenumaladoddi Jayasimha & R. Venkata Siva Reddy, A Robust Face Emotion Recognition Approach through Optimized SIFT Features and Adaptive Deep Belief Neural Network, Journal of Applied Security Research, 2019, DOI:
10.1080/19361610.2019.1656471
.
This article contains extensive and continuous content similarity across all sections with the previously published article: Yenumaladoddi Jayasimha & R. Venkata Siva Reddy (2019) A robust face emotion recognition approach through optimized SIFT features and adaptive deep belief neural network, Intelligent Design Technologies, 13.3, 379-390. DOI:
10.3233/IDT-190022
.
The substantial similarity between the articles is not acknowledged.
Following a request by the corresponding author to withdraw this article from Journal of Applied Security research, we discovered the previously published article. We contacted the corresponding author multiple times but have received no response. Therefore, we have determined that retracting this article is the best course of action.
We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.
The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as "Retracted." |
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ISSN: | 1936-1610 1936-1629 |
DOI: | 10.1080/19361610.2019.1656471 |