تحسين كفاءة وأمن عمليات مراقبة جوازات السفر في المطارات باستخدام نموذج الكشف عن الأجسام R-CNN

Rajapaksha A, Jayasuriya N. Smart Airport: A Review on Future of the Airport Operation. Glob J Manag Bus Res. 2020 Jan 15; 20(A3): 25–34. https://journalofbusiness.org/index.php/GJMBR/article/view/3027

Wiener EL, Nagel DC. Human Factors in Aviation. Gulf Prof Pub; 1988. 884 p. https://www.elsevier.com/books/human-factors-in-aviation/wiener/978-0-88415-164-3

Mehul M, Kant H Kamal, Gaurav M, Paawan S. Machine Learning and Deep Learning in Real-Time Applications. IGI Global; 2020. 364 p. https://doi.org/10.4018/978-1-5225-9643-1

Janssen S, Sharpanskykh A, Curran R. Agent-based modelling and analysis of security and efficiency in airport terminals. Transp Res Part C Emerg Technol. 2019 Mar 1; 100: 142–60. https://www.sciencedirect.com/science/article/pii/S0968090X1830809X

Liu Y, Liu Z, Jia R. DeepPF: A deep learning based architecture for metro passenger flow prediction. Transp Res Part C Emerg Technol. 2019 Apr 1; 101: 18–34. https://www.sciencedirect.com/science/article/pii/S0968090X18306806

Misra I, Maaten L van der. Self-Supervised Learning of Pretext-Invariant Representations. Proc IEEE/CVF conf comput vis Pattern Recognit. 2020. p. 6707–17. https://openaccess.thecvf.com/content_CVPR_2020/html/Misra_Self-Supervised_Learning_of_Pretext-Invariant_Representations_CVPR_2020_paper.html

Samuel AL. Some Studies in Machine Learning Using the Game of Checkers. II—Recent Progress. In: Levy DNL, editor. Computer Games I. New York, NY: Springer; 1988. p. 366–400. https://doi.org/10.1007/978-1-4613-8716-9_15

Simon HA. Administrative Behavior, 4th Edition. Simon and Schuster; 2013. 390 p. https://www.simonandschuster.com/books/Administrative-Behavior/Herbert-A-Simon/9780684835822

Miikkulainen R, Liang J, Meyerson E, Rawal A, Fink D, Francon O, et al. Chapter 15 - Evolving Deep Neural Networks. In: Kozma R, Alippi C, Choe Y, Morabito FC, editors. Artificial Intelligence in the Age of Neural Networks and Brain Computing. Academic Press; 2019. p. 293–312. https://www.sciencedirect.com/science/article/pii/B9780128154809000153

Botchkarev A. A New Typology Design of Performance Metrics to Measure Errors in Machine Learning Regression Algorithms. Interdiscip J Inf Knowl Manag. 2019 Jan 24;14:045–76. https://www.informingscience.org/Publications/4184

Das A, Azad Rabby AS, Kowsar I, Rahman F. A Deep Learning-based Unified Solution for Character Recognition. Inter Conf Pat Reco (ICPR). 2022. p. 1671–7. https://doi.org/10.1109/ICPR48806.2022.9413534

Wu M, Li C, Yao Z. Deep Active Learning for Computer Vision Tasks: Methodologies, Applications, and Challenges. Appl Sci. 2022 Jan ; 12(16): 8103. https://www.mdpi.com/2076-3417/12/16/8103

Bhatia R, Jain A, Chan E. Smart airports: A comprehensive review of emerging technologies and future directions. J Air Transp Manag. 2021; 91: 101994. https://doi.org/10.1016/j.jairtraman.2020.101994

Omran M, AlShemmary EN. An iris recognition system using deep convolutional neural network. J Phy: Conf ser. 2020 May; 1530(1): 012159. IOP Publishing. https://doi.org/10.1088/1742-6596/1530/1/012159

Finizola JS, Targino JM, Teodoro FGS, de Moraes Lima CA. A Comparative Study between Deep Learning and Traditional Machine Learning Techniques for Facial Biometric Recognition. Ibero-Am Conf Artif Intell. 2018: 217–28. https://doi.org/10.1007/978-3-030-03928-8_18

Ayvaz S, Alpay K. Predictive maintenance system for production lines in manufacturing: A machine learning approach using IoT data in real-time. Expert Syst Appl. 2021 Jul 1; 173: 114598. https://www.sciencedirect.com/science/article/pii/S0957417421000397

Kallel A, Rekik M, Khemakhem M. IoT-fog-cloud based architecture for smart systems: Prototypes of autism and COVID-19 monitoring systems. Softw Pract Exp. 2021; 51(1): 91–116. https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2924

Hassan FH, Omar MA. Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation. Baghdad Sci J. 2021 Dec 20; 18(4(Suppl.)): 1406–1406. https://doi.org/10.21123/bsj.2021.18.4(Suppl.).1406

Hazgui M, Ghazouani H, Barhoumi W. Genetic programming-based fusion of HOG and LBP features for fully automated texture classification. Vis Comput. 2022 Feb 1; 38(2): 457–76. https://doi.org/10.1007/s00371-020-02028-8

Abdollahi S, Pourghasemi HR, Ghanbarian GA, Safaeian R. Prioritization of effective factors in the occurrence of land subsidence and its susceptibility mapping using an SVM model and their different kernel functions. Bull Eng Geol Environ. 2019 Sep 1; 78(6): 4017–34. https://doi.org/10.1007/s10064-018-1403-6

Sun Y, Xue B, Zhang M, Yen GG, Lv J. Automatically Designing CNN Architectures Using the Genetic Algorithm for Image Classification. IEEE Trans Cybern. 2020 Sep; 50(9): 3840–54. https://doi.org/10.1109/TCYB.2020.2983860

Mekhalfi ML, Nicolò C, Bazi Y, Al Rahhal MM, Alsharif NA, Al Maghayreh E. Contrasting YOLOv5, transformer, and EfficientDet detectors for crop circle detection in desert. IEEE Geosci Remote Sens Lett. 2021 Jun 14; 19: 1-5. https://doi.org/10.1109/LGRS.2021.3085139.

Zhai S, Shang D, Wang S, Dong S. DF-SSD: An Improved SSD Object Detection Algorithm Based on DenseNet and Feature Fusion. IEEE Access. 2020; 8: 24344–57. https://doi.org/10.1109/ACCESS.2020.2971026.

Al-Mekhlafi ZG, Al-Shareeda MA, Manickam S, Mohammed BA, Qtaish A. Lattice-Based Lightweight Quantum Resistant Scheme in 5G-Enabled Vehicular Networks. Mathematics. 2023 Jan; 11(2): 399. https://doi.org/10.3390/math11020399

Mohammed BA, Al-Shareeda MA, Manickam S, Al-Mekhlafi ZG, Alreshidi A, Alazmi M, et al. FC-PA: Fog Computing-Based Pseudonym Authentication Scheme in 5G-Enabled Vehicular Networks. IEEE Access. 2023; 11: 18571–81. https://doi.org/10.1109/ACCESS.2023.3247222.

Al-Mekhlafi ZG, Al-Shareeda MA, Manickam S, Mohammed BA, Alreshidi A, Alazmi M, et al. Chebyshev Polynomial-Based Fog Computing Scheme Supporting Pseudonym Revocation for 5G-Enabled Vehicular Networks. Electronics. 2023 Jan; 12(4): 872. https://doi.org/10.3390/electronics12040872

Al-Shareeda MA, Manickam S. COVID-19 Vehicle Based on an Efficient Mutual Authentication Scheme for 5G-Enabled Vehicular Fog Computing. Int J Environ Res Public Health. 2022 Jan; 19(23): 15618. https://doi.org/10.3390/ijerph192315618

Sricharoenpramong S. Service quality improvement of ground staff at Don Mueang International Airport. Kasetsart J Soc Sci. 2018 Jan 1; 39(1): 15–21. https://doi.org/10.1016/j.kjss.2017.12.001

Abdulmunem IA, Harba ES, Harba HS. Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks. Baghdad Sci J. 2021 Dec 1; 18(4): 1317–1317. https://doi.org/10.21123/bsj.2021.18.4.1317

Hussain FS, Aljuboori AF. A Crime Data Analysis of Prediction Based on Classification Approaches. Baghdad Sci J. 2022 Oct 1; 19(5): 1073–1073. https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/6310

Alsaedi EM, Farhan A kadhim. Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption. Baghdad Sci J. 2023 Feb 1; 20(1): 0206–0206. https://doi.org/10.21123/bsj.2022.6550

Asroni A, Ku-Mahamud KR, Damarjati C, Slamat HB. Arabic Speech Classification Method Based on Padding and Deep Learning Neural Network. Baghdad Sci J. 2021 Jun 20; 18(2(Suppl.)): 0925–0925. https://doi.org/10.21123/bsj.2021.18.2(Suppl.).0925

Alkattan ZM, Aldabagh GMT. Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network. Baghdad Sci J. 2022 Oct 1; 19(5): 1100–1100. https://doi.org/10.21123/bsj.2022.6117

Hassan NF, Abdulrazzaq HI. Pose Invariant Palm Vein Identification System using Convolutional Neural Network. Baghdad Sci J. 2018 Dec 9; 15(4): 0502–0502. https://doi.org/10.21123/bsj.2018.15.4

Hasan MM, Ibraheem NA. Hybrid Cipher System using Neural Network. Baghdad Sci J . 2008 Sep 7 5(3): 460–71. https://doi.org/10.21123/bsj.2008.5.3.460-471

Schott L, Rauber J, Bethge M, Brendel W. Towards the first adversarially robust neural network model on MNIST . arXiv; 2018. http://arxiv.org/abs/1805.09190

Mu N, Gilmer J. MNIST-C: A Robustness Benchmark for Computer Vision. arXiv; 2019. http://arxiv.org/abs/1906.02337

Bharati P, Pramanik A. Deep Learning Techniques—R-CNN to Mask R-CNN: A Survey. Computational Intelligence in Pattern Recognition. Singapore: Springer; 2020. p. 657–68. https://doi.org/10.1007/978-981-15-3506-7_56

Wu L, He D, Ai B, Wang J, Qi H, Guan K, et al. Artificial Neural Network Based Path Loss Prediction for Wireless Communication Network. IEEE Access. 2020; 8: 199523–38. https://doi.org/ 10.1109/ACCESS.2020.3033998

Sherstinsky A. Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network. Phys Nonlinear Phenom. 2020 Mar 1; 404: 132306. https://www.sciencedirect.com/science/article/pii/S0167278919305974