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A New Hybrid Model to Predict Human Age Estimation from Face Images Based on Supervised Machine Learning Algorithms Cover

A New Hybrid Model to Predict Human Age Estimation from Face Images Based on Supervised Machine Learning Algorithms

Open Access
|Jun 2023

References

  1. Xie, J.-C., C.-M. Pun. Deep and Ordinal Ensemble Learning for Human Age Estimation from Facial Images. – IEEE Transactions on Information Forensics and Security, Vol. 15, 2020, pp. 2361-2374.
  2. Cao, W., V. Mirjalili, S. Raschka. Rank Consistent Ordinal Regression for Neural Networks with Application to Age Estimation. – Pattern Recognition Letters, Vol. 140, 2020, pp. 325-331.
  3. Liu, X., et al. Face Image Age Estimation Based on Data Augmentation and Lightweight Convolutional Neural Network. – Symmetry, Vol. 12, 2020, No 1, 146.
  4. Bekhouche, S. E., et al. A Comparative Study of Human Facial Age Estimation: Handcrafted Features vs. Deep Features. – Multimedia Tools and Applications, Vol. 79, 2020, No 35, pp. 26605-26622.
  5. Zhu, H., et al. Ordinal Distribution Regression for Gait-Based Age Estimation. – Science China Information Sciences, Vol. 63, 2020, No 2, pp. 1-14.
  6. Xia, M., et al. Multi-Stage Feature Constraints Learning for Age Estimation. – IEEE Transactions on Information Forensics and Security, Vol. 15, 2020, pp. 2417-2428.
  7. Tiwari, R. K. Human Age Estimation Using Machine Learning Techniques. – International Journal of Electronics Engineering and Applications, Vol. 8, 2020, No 1, pp. 01-09.
  8. Fayyad, U., G. Shapiro, P. Smyth. From Data Mining to Knowledge Discovery in Databases. – AI Magazine, Vol. 17, 1996, No 3, pp. 37-54.
  9. Suo, J., T. Wu, S. Zhu, S. Shan, X. Chen, W. Gao. Design Sparse Features for Age Estimation Using Hierarchical Face Model. – In: Proc. of IEEE Conf. on FGR, 2008, pp. 1-6.
  10. Stone, A. The Aging Process of the Face & Techniques of Rejuvenation, 2012 (Accessed 10/4/2015). http://www.aaronstonemd.com/FacialAging Rejuvenation.htm
  11. Lanitis, A. A Survey of the Effects of Aging on Biometric Identity Verification. – International Journal of Biometrics (IJBM), Vol. 2, 2012, No 1, pp. 34-52.
  12. Ranjan, J., D. Datta, R. Saha. Age Estimation from Face Image Using Wrinkle Features. – In: Proc. of International Conference on Information and Communication Technologies (ICICT’14), 3-5 December 2014, Bolgatty Palace & Island Resort, Kochi, India.
  13. Geng, X., Z. H. Zhou, Y. Zhang, G. Li, H. Dai. Learning from Facial Aging Patterns for Automatic Age Estimation. – In: Proc. of ACM International Conference on Multimedia, New York, NY, USA, 2014, pp. 307-316.
  14. Grd, P., M. Bača. Creating a Face Database for Age Estimation and Classification. – In: Proc. of 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO’16), IEEE, 2016.
  15. Rothe, R., R. Timofte, L. V. Gool. DEX: Deep Expectation of Apparent Age from a Single Image. – In: Proc. of IEEE International Conference on Computer Vision Workshops, 2015.
  16. Fu, Y., G. Guo, T. S. Huang. Age Synthesis and Estimation via Faces: A Survey. – IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, 2010, No 11, pp. 1955-1976.
  17. Lim, S. Estimation of Gender and Age Using CNN-Based Face Recognition Algorithm. – International Journal of Advanced Smart Convergence, Vol. 9, 2020, No 2, pp. 203-211.
  18. Shejul, A. A., K. S. Kinage. Deep Appearance Model and Crow-Sine Cosine Algorithm-Based Deep Belief Network for Age Estimation. – International Journal of Ambient Computing and Intelligence (IJACI), Vol. 12, 2021, No 3, pp. 185-207.
  19. Guehairia, O., et al. Feature Fusion via Deep Random Forest for Facial Age Estimation. – Neural Networks, Vol. 130, 2020, pp. 238-252.
  20. Micheal, A. A., P. Geetha. A Novel Hybrid Feature Framework for Multi-View Age Estimation. – Applied Artificial Intelligence, Vol. 35, 2021, No 15, pp. 1361-1387.
  21. Angulu, R., J. R. Tapamo, A. O. Adewumi. Age Estimation via Face Images: A Survey. – EURASIP Journal on Image and Video Processing, Vol. 2018, 2018, No 1, pp. 1-35.
  22. Shejul, A. A., K. S. Kinage. Deep Appearance Model and Crow-Sine Cosine Algorithm-Based Deep Belief Network for Age Estimation. – International Journal of Ambient Computing and Intelligence (IJACI), Vol. 12, 2021, No 3, pp. 185-207.
  23. Khajavi, M., A. Ahmadyfard. Human Face Aging Based on Active Appearance Model Using Proper Feature Set. – Signal, Image and Video Processing, 2022, pp. 1-9.
  24. Shejul, A. A., K. S. Kinage, B. E. Reddy. Facial Based Human Age Estimation Using Deep Belief Network. – In: Proc. of EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing, Cham, Springer, 2020.
  25. Wang, H., V. Sanchez, C.-T. Li. Improving Face-Based Age Estimation with Attention-Based Dynamic Patch Fusion. – IEEE Transactions on Image Processing, Vol. 31, 2022, pp. 1084-1096.
  26. Qian, W., et al. Label Distribution Feature Selection with Feature Weights Fusion and Local Label Correlations. – Knowledge-Based Systems, Vol. 256, 2022, 109778.
  27. Lu, D., et al. Age Estimation from Facial Images Based on Gabor Feature Fusion and the CIASO‐SA Algorithm. – CAAI Transactions on Intelligence Technology, 2022.
  28. Greco, A., et al. Effective Training of Convolutional Neural Networks for Age Estimation Based on Knowledge Distillation. – Neural Computing and Applications, 2021, pp. 1-16.
  29. Rwigema, J., J. Mfitumukiza, K. Tae-Yong. A Hybrid Approach of Neural Networks for Age and Gender Classification through Decision Fusion. – Biomedical Signal Processing and Control, Vol. 66, 2021, 102459.
  30. Al-Dujaili, M. J., A. Ebrahimi-Moghadam. Speech Emotion Recognition: A Comprehensive Survey. – Wireless Personal Communications, 2023, pp. 1-37.
  31. Madhavi, A., et al. Human Age Estimation Using Support Vector Machine. – In: Machine Learning Technologies and Applications, Singapore, Springer, 2021. pp. 273-286.
  32. Micheal, A. A., P. Geetha. A Novel Hybrid Feature Framework for Multi-View Age Estimation. – Applied Artificial Intelligence, Vol. 35, 2021, No 15, pp. 1361-1387.
  33. Al-Dujaili, M. J., M. T. Mezeel. Novel Approach for Reinforcement the Extraction of ECG Signal for Twin Fetuses Based on Modified BSS. – Wireless Personal Communications, Vol. 119, 2021, No 3, pp. 2431-2450.
  34. Al_Dujaili, M. J., H. T. H. S. ALRikabi, I. R. N. ALRubeei. Gender Recognition of Human from Face Images Using Multi-Class Support Vector Machine (SVM) Classifiers. – International Journal of Interactive Mobile Technologies, Vol. 17, 2023, No 8.
  35. Lee, J.-S., et al. Age Estimation Using Correlation-Refined Features of Convolutional Neural Network. – Journal of Information Science & Engineering, Vol. 37, 2021, No 6.
  36. Al Dujaili, M. J., A. Ebrahimi-Moghadam, A. Fatlawi. Speech Emotion Recognition Based on SVM and KNN Classifications Fusion. – International Journal of Electrical and Computer Engineering, Vol. 11, 2021, No 2, 1259.
DOI: https://doi.org/10.2478/cait-2023-0011 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 20 - 33
Submitted on: Jan 26, 2023
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Accepted on: May 12, 2023
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Published on: Jun 12, 2023
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Mohammed Jawad Al-Dujaili, Hydr jabar sabat Ahily, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.