Open AccessCorrection

Correction: Kumar et al. Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System. Sensors 2022, 22, 5160

Sandeep Kumar

^1,*

Shilpa Rani

²,

Arpit Jain

³,

Chaman Verma

⁴

Maria Simona Raboaca

^5,6,*

Zoltán Illés

⁴ and

Bogdan Constantin Neagu

⁷

Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Vijaywada 522302, India

Department of IT, Neil Gogte Institute of Technology, Kachawanisingaram Village, Hyderabad 500039, India

College of Computing Sciences and IT, Teerthanker Mahaveer University, Moradabad 244001, India

⁴

Department of Media and Educational Informatics, Faculty of Informatics, Eötvös Loránd University, 1053 Budapest, Hungary

⁵

National Research and Development Institute for Cryogenic and Isotopic Technologies—ICSI Rm, 240050 Ramnicu Valcea, Romania

⁶

Doctoral School, Polytechnic University of Bucharest, 313 Splaiul Independentei, 060042 Bucharest, Romania

⁷

Department of Power Engineering, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania

Authors to whom correspondence should be addressed.

Sensors 2023, 23(21), 8825; https://doi.org/10.3390/s23218825

Submission received: 12 September 2023 / Accepted: 21 September 2023 / Published: 30 October 2023

(This article belongs to the Section Intelligent Sensors)

Download Versions Notes

Missing Citation

In the original publication [1], references [64,65] were not cited. The citation has now been inserted in Section 5. Results, Section 5.1. Dataset Overview, paragraph 1 and should read as follows:

For the sample, the author used his own images for the validation of the proposed work in real-time. For the evaluation of the proposed work, six publicly available benchmark datasets were used. These included NUAA and CASIA for Face Spoofing, Adience and IOG for Age, Adience and IOG for Gender and CK+ and JAFFE [64,65] for Facial Expression for a human face after signing the agreement for their respective organizations. We created a combined dataset for each module, i.e., first module for spoofing (in both the datasets, we have 14K images approximately), the second module for age and gender (in both the datasets, we have 31K approximately) and the last module for facial expression (in both the datasets, we have 11K approximately) and then trained our model on these datasets. The entire description of the benchmark datasets is shown in Table 4.

The citation has also been inserted in Section 5. Results, Section 5.3. Evaluation Results in Terms of Accuracy, paragraph 4 and should read as follows:

Fourth Module: Finally, in the fourth module, the proposed work is evaluated for various facial expressions on benchmark datasets, i.e., CK+ and JAFFE [64,65]. According to Tables 8 and 9, it is very clear that the proposed algorithm achieved better accuracy for all various expressions, i.e., anger, disgust, happiness, natural, sadness and surprise. The graphical representations of facial expression are shown in Figures 17 and 18.

References

References 64 and 65 were inserted:

64. Lyons, M.J.; Kamachi, M.; Gyoba, J. Coding Facial Expressions with Gabor Wavelets (IVC Special Issue). arXiv 2020, arXiv:2009.05938. https://doi.org/10.48550/arXiv.2009.05938.

65. Lyons, M.J. “Excavating AI” Re-excavated: Debunking a Fallacious Account of the JAFFE Dataset. arXiv 2021, arXiv:2107.13998. https://doi.org/10.48550/arXiv.2107.13998.

The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

Kumar, S.; Rani, S.; Jain, A.; Verma, C.; Raboaca, M.S.; Illés, Z.; Neagu, B.C. Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System. Sensors 2022, 22, 5160. [Google Scholar]

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Share and Cite

MDPI and ACS Style

Kumar, S.; Rani, S.; Jain, A.; Verma, C.; Raboaca, M.S.; Illés, Z.; Neagu, B.C. Correction: Kumar et al. Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System. Sensors 2022, 22, 5160. Sensors 2023, 23, 8825. https://doi.org/10.3390/s23218825

AMA Style

Kumar S, Rani S, Jain A, Verma C, Raboaca MS, Illés Z, Neagu BC. Correction: Kumar et al. Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System. Sensors 2022, 22, 5160. Sensors. 2023; 23(21):8825. https://doi.org/10.3390/s23218825

Chicago/Turabian Style

Kumar, Sandeep, Shilpa Rani, Arpit Jain, Chaman Verma, Maria Simona Raboaca, Zoltán Illés, and Bogdan Constantin Neagu. 2023. "Correction: Kumar et al. Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System. Sensors 2022, 22, 5160" Sensors 23, no. 21: 8825. https://doi.org/10.3390/s23218825

APA Style

Kumar, S., Rani, S., Jain, A., Verma, C., Raboaca, M. S., Illés, Z., & Neagu, B. C. (2023). Correction: Kumar et al. Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System. Sensors 2022, 22, 5160. Sensors, 23(21), 8825. https://doi.org/10.3390/s23218825

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Menu

Correction: Kumar et al. Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System. Sensors 2022, 22, 5160

Missing Citation

References

Reference

Share and Cite

Article Metrics

Article Access Statistics

Further Information

Guidelines

MDPI Initiatives

Follow MDPI