التنبؤ بسنوات إنتاج الأفلام من خلال التعرف على وجوه الممثلين باستخدام التعلم الآلي

Cihang X, Mingxing T, Boqing G, Jiang W, Alan Y, Quoc V. L. Adversarial Examples Improve Image Recognition. Proc. IEEE Comput Soc Conf Comput Vis Pattern Recognit. 2020: 819-828. https://doi.org/10.1109/CVPR42600.2020.00090

Ahmed M E, Mahmoud Y S, Nora E, Abdelghafar M E, Samaa M S, Zahraa T. Bayesian Optimization with Support Vector Machine Model for Parkinson Disease Classification. Sensors (MDPI). 2023; 23(4): 2085-2106. https://doi.org/10.3390/s23042085

Farah A A, Nada A Z A. A Survey on Arabic Text Classification Using Deep and Machine Learning Algorithms. Iraqi J Sci. 2022; 63(1): 409-419. https://doi.org/10.24996/ijs.2022.63.1.37

Rahul N, Anil D. Face Recognition Using SVM Based Machine Learning: A Review. Webology. 2021; 18(6): 2375- 2384.

Xinyi W, Jianteng P, Sufang Z, Bihui C, Yi W, Yandong G. A Survey of Face Recognition. arXiv preprint arXiv:2212.13038. 1-59. https://doi.org/10.48550/arXiv.2212.13038

Tiago F P, Dominic S, Yu L, Xinyi Z, S´ebastien M, Manuel G. Eight Years of Face Recognition Research: Reproducibility, Achievements and Open Issues. arXiv preprint arXiv:2202;04040: 1-15. https://doi.org/10.48550/arXiv.2208.04040

Kai G, Shuai W, Yong X. Face recognition using both visible light image and near-infrared image and a deep network. Trans Intell Technol. 2017; 2 (1): 39-47. https://doi.org/10.1016/j.trit.2017.03.001

Fahima T, Imdadul Islam M, Risala T, Amin M. Human Face Recognition with Combination of DWT and Machine Learning. J. King Saud Univ. 2022; 34(3): 546-556. https://doi.org/10.1016/j.jksuci.2020.02.002

Omkar M, Andrea V, Andrew Z. Deep Face Recognition. Proc Br Mach Vis Conf. 2015: 1-12. https://doi.org/10.5244/c.29.41

10. Laith R F, Shaimaa A. A Face Recognition System Based on Principal Component Analysis-Wavelet and Support Vector Machines. Cihan Univ Erbil Sci J. 2019; 3(2): 14-20. https://doi.org/10.24086/cuesj.v3n2y2019.pp14-20

Meenakshi S, Siva Jothi M, Murugan D.Face Recognition using Deep Neural Network Across Variationsin Pose and Illumination. Int J Recent Technol Eng. 2019; 8(1S4): 289-29 . https:// https://doi.org/10.1007/978-981-10-5152-4_3

Putta S, Venkatramaphanikumar S, Krishna K. Scale Invariant Face Recognition with Gabor Wavelets and SVM. Int J Recent Technol Eng. 2019; 7(5S4): 100-104.

Ni K, Praba H, Ni P, Komang D, Putu B, I Putu D. Face Identification Based on K-Nearest Neighbor. Sci J Inform. 2019; 6(1): 150-159. https://doi.org/10.15294/sji.v6i2.19503

Zhiming X, Junjie L, Hui S. A Face Recognition Method Based on CNN. High Performance Computing and Computational Intelligence Conference. J Phys.: Conf Ser. 2019; 1395(1): 012006. https://doi.org/10.1088/1742-6596/1395/1/012006

Muhammad S F, Muhammad A Z, Zahid J, Imran M, Saqib A. A Comparative Analysis Using Different Machine Learning: An Efficient Approach for Measuring Accuracy of Face Recognition. Int J Mach Learn. 2021; 11(2): 115-120. https://doi.org/10.18178/ijmlc.2021.11.2.1023

Yohanssen P, Lit M G, Emma H, Ade E R. Face recognition for presence system by using residual networks-50 architecture. Int J Electr Comput Eng.2021; 11(6): 5488-5496. https://doi.org/10.11591/ijece.v11i6.pp5488-5496

Benradi H, Chater A, Lasfar A. Face recognition method combining SVM machine learning and scale invariant feature transform. 10th International Conference on Innovation, Modern Applied Science & Environmental Studies. E3S Web Conf. 2022; 351(01033): 1–5. https://doi.org/10.1051/e3sconf/202235101033

Zahraa M N, Mushtaq T M, Shaymaa A S. Face Recognition Method based on Support Vector Machine and Rain Optimization Algorithm (ROA). Webology. 2022; 19(1): 2170–2181. https://doi.org/10.14704/WEB/V19I1/WEB19147

Ahmed A. N., Nazlia O., Zohaa M. A. Artificial Neural Network and Latent Semantic Analysis for Adverse Drug ReactionDetection. Baghdad Sci J. 2024; 21(1): 226-233. https://dx.doi.org/10.21123/bsj.2023.7988

Safa S A, Alaa k F, Alexander S L. A Comparative Study of Anemia Classification Algorithms for International and Newly CBC Datasets. Int J Biomed Eng. 2023; 19(06): 141–157. https://doi.org/10.3991/ijoe.v19i06.38157

Khaled M, Ahmad T, Mohammed E. Multimodal student attendance management system (MSAMS). Ain Shams Eng J. 2018; 9(4): 2917-2929. https://doi.org/10.1016/j.asej.2018.08.002

Sravan G, Adrian G B. Ortho-diffusion Decompositions for Face Recognition from Low Quality Images. IEEE Int Conf. Image Process. 2015; 3625 – 3629. https://doi.org/10.1109/ICIP.2015.7351480

Sarah G E, Ibrahim E E, Taysir H A. Embedding-Based Deep Neural Network and Convolutional Neural Network Graph Classifiers. Electronics. 2023; 12(12): 2715. https://doi.org/10.3390/electronics12122715

Yao-Hung HT, Liang-Kang H, Ruslan S. Learning Robust Visual-Semantic Embeddings. IEEE Int Conf Comput Vis. 2017; 3591-3600. https://doi.org/10.1109/ICCV.2017.386

Ali N. R, Rozaida G. Human Face Recognition Based on Local Ternary Pattern and Singular Value Decomposition. Baghdad Sci J. 2022; 19(5): 1090-1099.

Suwarno S, Kevin K. Analysis of Face Recognition Algorithm: Dlib and OpenCV. J Inf Telecommun Eng. 2020; 4(1): 173-184. https://doi.org/10.31289/jite.v4i1.3865

Kevin S, Gede P K. Face Recognition Using Modified OpenFace. Procedia Computer Science. 3rd International Conference on Computer Science and Computational Intelligence. 2018; 135: 510–517. https://doi.org/10.1016/j.procs.2018.08.203

Florian S, Dmitry K, James P. FaceNet: A Unified Embedding for Face Recognition and Clustering. IEEE Conf. Comput Vis Pattern Recog. 2015: 815-823. https://doi.org/10.1109/CVPR.2015.7298682

Filiberto P, Jesus O, Gabriel S, Gibran B. Lidia P T, Osvaldo L G. Analysis of Real-Time Face-Verification Methods for Surveillance Applications. MDPI. J Imaging. 2023; 9(2): 21. https://doi.org/10.3390/jimaging9020021

Wen Chang C, Hung Chou H, Yung Fa H, Li Hua L. Combining Classifiers for Deep Learning Mask Face Recognition. MDPI. Info. 2023; 14(7):421. https://doi.org/10.3390/info14070421

Tadas B, Peter R, Louis-Philippe M. OpenFace 2.0: Facial behavior analysis toolkit. Proceedings of the 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition. 2018; 59-66. https://doi.org/10.1109/WACV.2016.7477553

Forrest N I, Song H, Matthew W M, Khalid A, William J D, Kurt K. SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and< 0.5 MB model size. ICLR. arXiv preprint arXiv:1602.07360v4. 2016: 1-13. https://doi.org/10.48550/arXiv.1602.07360

Kaiyu Y, Klint Q, Li F, Jia D, Olga R. Towards Fairer Datasets: Filtering and Balancing the Distribution of the People Subtree in the ImageNet Hierarchy. Conference on Fairness, Accountabiility and Transparency (FAT). 2020: 547-558. https://doi.org/10.1145/3351095.3375709

Alex K, Ilya S, Geoffrey E H. ImageNet classification with deep convolutional neural networks. Commun ACM. 2017; 60(6): 84–90. https://doi.org/10.1145/3065386

Olga R, Jia D, Hao S, Jonathan K. ImageNet Large Scale Visual Recognition Challenge. Int J Comput Vis Pattern Recognit. 2015; 115(3): 211-252. https://doi.org/10.48550/arXiv.1409.0575

Simonyan, K., & Zisserman, A. Very deep convolutional networks for large-scale image recognition. Int J Comput. Vis. Pattern Recognit. 2015. https://doi.org/10.48550/arXiv.1409.1556

David H, Douglas Eck. A Neural Representation of Sketch Drawings. Proc Int Conf Learn Represent. 2017: 1–16. https://doi.org/10.48550/arXiv.1704.03477

José J A, Casper K S, Søren K S, Henrik N, Ole W. DeepLoc: prediction of protein subcellular localization using deep learning . Bioinformatics. 2017; 33(21): 3387–3395. https://doi.org/10.1093/bioinformatics/btx431

Anil K Y, Rajesh K P, Nirmal K G, Punit G, Dinesh K S, Mohammad A . Hybrid Machine Learning Model for Face Recognition Using SVM. Comput Mater Contin. 2022; 72(2): 2697-2712. https://doi.org/10.32604/cmc.2022.023052

Ashraf A. A, Tawfeeq M. T, Marwa A. A. Constructing a Software Tool for Detecting Face Mask-wearing by Machine Learning. Baghdad Sci J. 2022; 19(3): 642-653. http://dx.doi.org/10.21123/bsj.2022.19.3.0642

Vinay A, Abhijay G, Aprameya B, Arvind S, Kannamedi B. M, Natarajan S. Unconstrained Face Recognition using Bayesian Classification. 8th Int Conf Adv Comput Commun. 2018; 143: 519-527. https://doi.org/10.1016/j.procs.2018.10.425

Abita D, Kantesh K. G, Heena G. Naive Bayes Classification Based Facial Expression Recognition With Kernel PCA Features. Int J Eng Dev Res. 2017; 5(3): 326-330.

Kaarthik K, Madhumitha J, Narmatha T, Selva B. S. Face Detection and Recognition Using Naïve Bayes Algorithm. Int J Disast Recov Bus Contin. 2020; 11(1): 11-18.

Mohammad R. H, Soikot S, Moqsadur R. Different Machine Learning based Approaches of Baseline and Deep Learning Models for Bengali News Categorization. Int J Comput Appl· 2020; 176(18): 10-16. https://doi.org/10.5120/ijca2020920107

Yu M, HuaJun W, Jun W, ZhenHeng W, Yao Y, Cong H. Design and implementation of face recognition system based on convolutional neural network. J Phys Conf Ser. 2021; 2029(1): 1-6. https://doi.org/10.1088/1742-6596/2029/1/012096

Ansam H R, Muthana H H. Robust Detection and Recognition System Based on Facial Extraction and Decision Tree. J Eng Sustain Dev. 2021; 25(4): 40-50. https://doi.org/10.31272/jeasd.25.4.4

Hana'a M S, Rana T R. Smart Door for Handicapped People via Face Recognition and Voice Command Technique. Eng Technol J. 2021; 39(1): 222-230. https://doi.org/10.30684/etj.v39i1B.1719

Su M. S, Khin M. S. Approaching Rules Induction: CN2 Algorithm in Categorizing of Biodiversity. Int J Trend Sci Res Dev. 2019; 3(4): 1581-1584.

Vinay A, Abhijay G, Vinayaka R K, Aprameya B, Arvind S, Kannamedi B M. et al. Facial Analysis Using Jacobians and Gradient Boosting. Int Conf Math Model Sci Comput Appl. 2020; 308: 393-404. https://doi.org/10.1007/978-981-15-1338-1_29

Bong-Hyun K. Implementation of Access Control System based on Face Prediction and Face Tracking. J Syst Manag Sci. 2022; 12(2); 367-377. https://doi.org/10.33168/JSMS.2022.0219

Wang C, Xue P, Li G, Wu Q. A Comparative Study of Face Recognition Classification Algorithms. Int J Adv. Netw. 2020; 5(3): 23-29. https://doi.org/10.21307/ijanmc-2020-024

Sumithra R, Gurua D S, Manjunath A, Anitha R. Children Longitudinal Face Recognition Using Random Forest. Int Conf IoT Comput Vis Bioeng. 2020; 542-551. http://dx.doi.org/10.2139/ssrn.3735819