FaceNet recognition algorithm subject to multiple constraints: Assessment of the performance
Literature has it that the performance of most face recognition algorithms still decline in multiple constrained environments (Occlusions and Expressions), despite the achieved successes of deep learning face recognition algorithms. Using expression variant test face images synthetically occluded at...
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| Veröffentlicht in: | Scientific African Jg. 23; S. e02007 |
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Elsevier B.V
01.03.2024
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| Abstract | Literature has it that the performance of most face recognition algorithms still decline in multiple constrained environments (Occlusions and Expressions), despite the achieved successes of deep learning face recognition algorithms. Using expression variant test face images synthetically occluded at 30% and 40% rates, the study evaluated the performance of FaceNet deep learning model for face recognition under the aforementioned constraints and when three (3) statistical multiple imputation methods (Multivariable Imputation using Chain Equations (MICE), MissForest and Regularized Expectation Maximization (RegEM)) are adopted for occlusion recovery. Results of the study showed improved recognition rates of the study algorithm when the imputation-based recovered faces were used for recognition compared with using their multiple constrained counterparts. However, test faces reconstructed with the MissForest imputation method were more accurately recognized using the FaceNet deep learning algorithm. Furthermore, the study demonstrated that some simple augmentation schemes sufficed to further enhance the performance of the FaceNet model. Specifically, the FaceNet algorithms gave the highest average recognition rates (85.19% and 79.5% for 30% and 40% occlusion levels respectively) under augmentation scheme IV (slight rotations, horizontal flipping, shearing, brightness adjustments, and stretching) using MissForest as the de-occlusion mechanism. The study also found that, no disparity existed in its performance with the choice of either Support Vector Machines (SVM) or City Block (CB) for classification under augmentation scheme IV. The study recommends using the MissForest imputation method in dealing with moderately high occluded test faces with varying expressions to enhance the performance of the FaceNet face recognition model. |
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| AbstractList | Literature has it that the performance of most face recognition algorithms still decline in multiple constrained environments (Occlusions and Expressions), despite the achieved successes of deep learning face recognition algorithms. Using expression variant test face images synthetically occluded at 30% and 40% rates, the study evaluated the performance of FaceNet deep learning model for face recognition under the aforementioned constraints and when three (3) statistical multiple imputation methods (Multivariable Imputation using Chain Equations (MICE), MissForest and Regularized Expectation Maximization (RegEM)) are adopted for occlusion recovery. Results of the study showed improved recognition rates of the study algorithm when the imputation-based recovered faces were used for recognition compared with using their multiple constrained counterparts. However, test faces reconstructed with the MissForest imputation method were more accurately recognized using the FaceNet deep learning algorithm. Furthermore, the study demonstrated that some simple augmentation schemes sufficed to further enhance the performance of the FaceNet model. Specifically, the FaceNet algorithms gave the highest average recognition rates (85.19% and 79.5% for 30% and 40% occlusion levels respectively) under augmentation scheme IV (slight rotations, horizontal flipping, shearing, brightness adjustments, and stretching) using MissForest as the de-occlusion mechanism. The study also found that, no disparity existed in its performance with the choice of either Support Vector Machines (SVM) or City Block (CB) for classification under augmentation scheme IV. The study recommends using the MissForest imputation method in dealing with moderately high occluded test faces with varying expressions to enhance the performance of the FaceNet face recognition model. |
| ArticleNumber | e02007 |
| Author | Appati, Justice K. Ocran, Eric Mensah, Joseph A. Boateng, Elijah K.A Asiedu, Louis |
| Author_xml | – sequence: 1 givenname: Joseph A. surname: Mensah fullname: Mensah, Joseph A. organization: Department of Computer Science, Ashesi University, No. 1 University Avenue, Berekuso, Eastern Region, Ghana – sequence: 2 givenname: Justice K. orcidid: 0000-0003-2798-4524 surname: Appati fullname: Appati, Justice K. organization: Department of Computer Science, College of Basic and Applied Sciences, University of Ghana, Ghana – sequence: 3 givenname: Elijah K.A surname: Boateng fullname: Boateng, Elijah K.A organization: Department of Computer Science, Ashesi University, No. 1 University Avenue, Berekuso, Eastern Region, Ghana – sequence: 4 givenname: Eric surname: Ocran fullname: Ocran, Eric organization: Department of Statistics and Actuarial Science, College of Basic and Applied Sciences, University of Ghana, Ghana – sequence: 5 givenname: Louis orcidid: 0000-0002-2859-1215 surname: Asiedu fullname: Asiedu, Louis email: lasiedu@ug.edu.gh organization: Department of Statistics and Actuarial Science, College of Basic and Applied Sciences, University of Ghana, Ghana |
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| Cites_doi | 10.3846/20294913.2012.661205 10.1016/j.chemolab.2012.11.010 10.1109/MSP.2010.936726 10.1186/s12874-020-01080-1 10.1155/2014/519158 10.1016/j.patcog.2008.10.010 10.1177/0962280216666564 10.1155/2021/7060270 10.3390/s19224933 10.1111/rssb.12279 10.1007/s00259-022-05746-4 10.1002/cpe.6629 10.1007/s42519-022-00292-6 10.1049/bme2.12029 10.1155/2020/9127465 10.20473/jisebi.7.1.22-30 10.1038/srep21689 10.1007/s10462-017-9578-y 10.17485/ijst/2017/v10i19/110646 10.1002/sim.8468 10.1016/j.inffus.2020.09.006 10.1016/S0262-8856(02)00009-4 10.1080/00401706.1979.10489751 10.11591/ijai.v11.i1.pp388-396 10.1109/CVPR.2015.7298682 10.1136/bmjopen-2013-002847 10.1155/2021/4981394 10.1093/aje/kwt312 10.3390/app12105195 10.1109/TSP.2004.831018 10.1145/2393216.2393308 10.1016/j.compeleceng.2020.106700 10.1145/3190618 10.1097/RLI.0b013e3182899104 10.1093/bioinformatics/btr597 10.1186/s40537-019-0197-0 10.1016/j.visres.2005.10.028 10.1016/j.jmir.2014.02.002 10.1109/CVPR46437.2021.01212 10.1080/00949655.2018.1530773 10.1001/jamainternmed.2018.7117 10.1186/1471-2288-14-28 10.1002/sim.5894 10.1109/CVPR.2016.527 10.1016/j.envint.2020.105713 10.1002/wics.49 |
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| Keywords | Occlusion Varying expressions MissForest Augmentation schemes MICE FaceNet algorithm RegEM |
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| References | H. Chen, Y. Wang, T. Guo, C. Xu, Y. Deng, Z. Liu, S. Ma, C. Xu, C. Xu, W. Gao, Pre-trained image processing transformer, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 12299–12310. Josphineleela, Raja Rao, Shaikh, Sudhakar (b22) 2023 Liu, Wang, Zou, Xia, Pang (b37) 2020; 139 Waljee, Mukherjee, Singal, Zhang, Warren, Balis, Marrero, Zhu, Higgins (b46) 2013; 3 Pisner, Schnyer (b55) 2020 Ganapathiraju, Hamaker, Picone (b58) 2004; 52 Deng, Da, Shao, Jiang (b4) 2020; 85 Tian, Shi, Liu (b56) 2012; 18 Chen, Chang, Chuang, Jeng (b62) 2022; 12 I. Kemelmacher-Shlizerman, S.M. Seitz, D. Miller, E. Brossard, The megaface benchmark: 1 million faces for recognition at scale, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4873–4882. Stekhoven, Bühlmann (b45) 2012; 28 Goren, Wilson (b5) 2006; 46 Mukkamala, Janoski, Sung (b57) 2002 Liu, Brown (b34) 2013; 120 Min, Hadid, Dugelay (b8) 2014; 2014 Jonsson, Kittler, Li, Matas (b59) 2002; 20 Resche-Rigon, White, Bartlett, Peters, Thompson, Group (b41) 2013; 32 Oyelade, Ezugwu (b21) 2022; 34 Liang, Jia, Xue, Li, Luo (b36) 2018; 80 Hong, Lynn (b44) 2020; 20 Chang, Lee, Lee, Yoon, Yu, Han, Choi (b13) 2013; 48 Lahasan, Lutfi, San-Segundo (b7) 2019; 52 Wang, Casalino, Khullar (b19) 2019; 179 Mensah, Asiedu, Mettle, Iddi (b65) 2021; 2021 Bovik (b31) 2010 Li, Prieto, Mery, Flynn (b1) 2018 Fessler (b11) 2010; 27 Vargas, Mosavi, Ruiz (b17) 2017 Alyüz, Gökberk, Spreeuwers, Veldhuis, Akarun (b6) 2012 Piccialli, Di Somma, Giampaolo, Cuomo, Fortino (b20) 2021; 66 A.K. Singh, G.C. Nandi, Face recognition using facial symmetry, in: Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology, 2012, pp. 550–554. Adhinata, Rakhmadani, Wijayanto (b28) 2021; 7 Wang (b54) 2005 Nakagawa, Ohtsuka (b60) 2022; 16 Resche-Rigon, White (b43) 2018; 27 William, Rachmawanto, Santoso, Sari (b50) 2019 G.B. Huang, M. Mattar, T. Berg, E. Learned-Miller, Labeled faces in the wild: A database forstudying face recognition in unconstrained environments, in: Workshop on Faces in‘Real-Life’Images: Detection, Alignment, and Recognition, 2008. Mammone, Turchi, Cristianini (b53) 2009; 1 Wu, Chen (b24) 2015 Le, Beuran, Tan (b35) 2018 Hughes, White, Seaman, Carpenter, Tilling, Sterne (b42) 2014; 14 Liu (b12) 2014; 45 F. Schroff, D. Kalenichenko, J. Philbin, Facenet: A unified embedding for face recognition and clustering, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 815–823. Asiedu, Mettle, Mensah (b32) 2020; 2020 Sundararajan, Woodard (b23) 2018; 51 Deng, Chang, Ido, Long (b40) 2016; 6 Shah, Bartlett, Carpenter, Nicholas, Hemingway (b48) 2014; 179 Galiano, Toledo, Blanes, Herranz, Batzelis (b61) 2022 Brownlee (b26) 2019; 21 Shorten, Khoshgoftaar (b49) 2019; 6 Slade, Naylor (b38) 2020; 39 Pain, Egan, Chen (b9) 2022; 49 Adhinata, Tanjung, Widayat, Pasfica, Satura (b29) 2022 Golla, Sharma (b30) 2019 Solaro, Barbiero, Manzi, Ferrari (b47) 2018; 88 Tabian, Fu, Sharif Khodaei (b10) 2019; 19 Chhabra, Vashisht, Ranjan (b39) 2017; 10 Ayiah-Mensah, Asiedu, Mettle, Minkah (b66) 2021; 2021 Cheon, Kim (b3) 2009; 42 Asiedu, Mensah, Ayiah-Mensah, Mettle (b14) 2021; 2021 Shinde, Shah (b16) 2018 Anwarul, Dahiya (b2) 2020 Golub, Heath, Wahba (b33) 1979; 21 Vu, Trieu, Nguyen (b27) 2022; 11 Zeng, Veldhuis, Spreeuwers (b64) 2021; 10 Animasaun, Shah, Wakif, Mahanthesh, Sivaraj, Koríko (b15) 2022 Shah (10.1016/j.sciaf.2023.e02007_b48) 2014; 179 Shinde (10.1016/j.sciaf.2023.e02007_b16) 2018 Min (10.1016/j.sciaf.2023.e02007_b8) 2014; 2014 Deng (10.1016/j.sciaf.2023.e02007_b4) 2020; 85 Chang (10.1016/j.sciaf.2023.e02007_b13) 2013; 48 Resche-Rigon (10.1016/j.sciaf.2023.e02007_b41) 2013; 32 Nakagawa (10.1016/j.sciaf.2023.e02007_b60) 2022; 16 Wu (10.1016/j.sciaf.2023.e02007_b24) 2015 William (10.1016/j.sciaf.2023.e02007_b50) 2019 Adhinata (10.1016/j.sciaf.2023.e02007_b29) 2022 Oyelade (10.1016/j.sciaf.2023.e02007_b21) 2022; 34 Fessler (10.1016/j.sciaf.2023.e02007_b11) 2010; 27 Goren (10.1016/j.sciaf.2023.e02007_b5) 2006; 46 Chhabra (10.1016/j.sciaf.2023.e02007_b39) 2017; 10 Stekhoven (10.1016/j.sciaf.2023.e02007_b45) 2012; 28 Galiano (10.1016/j.sciaf.2023.e02007_b61) 2022 Tabian (10.1016/j.sciaf.2023.e02007_b10) 2019; 19 Ayiah-Mensah (10.1016/j.sciaf.2023.e02007_b66) 2021; 2021 10.1016/j.sciaf.2023.e02007_b18 Vargas (10.1016/j.sciaf.2023.e02007_b17) 2017 Pain (10.1016/j.sciaf.2023.e02007_b9) 2022; 49 Josphineleela (10.1016/j.sciaf.2023.e02007_b22) 2023 Anwarul (10.1016/j.sciaf.2023.e02007_b2) 2020 Liu (10.1016/j.sciaf.2023.e02007_b12) 2014; 45 Solaro (10.1016/j.sciaf.2023.e02007_b47) 2018; 88 Chen (10.1016/j.sciaf.2023.e02007_b62) 2022; 12 Li (10.1016/j.sciaf.2023.e02007_b1) 2018 Pisner (10.1016/j.sciaf.2023.e02007_b55) 2020 Hughes (10.1016/j.sciaf.2023.e02007_b42) 2014; 14 Slade (10.1016/j.sciaf.2023.e02007_b38) 2020; 39 Wang (10.1016/j.sciaf.2023.e02007_b19) 2019; 179 Mensah (10.1016/j.sciaf.2023.e02007_b65) 2021; 2021 Alyüz (10.1016/j.sciaf.2023.e02007_b6) 2012 Liang (10.1016/j.sciaf.2023.e02007_b36) 2018; 80 Mammone (10.1016/j.sciaf.2023.e02007_b53) 2009; 1 Liu (10.1016/j.sciaf.2023.e02007_b34) 2013; 120 Ganapathiraju (10.1016/j.sciaf.2023.e02007_b58) 2004; 52 Vu (10.1016/j.sciaf.2023.e02007_b27) 2022; 11 Bovik (10.1016/j.sciaf.2023.e02007_b31) 2010 Le (10.1016/j.sciaf.2023.e02007_b35) 2018 Liu (10.1016/j.sciaf.2023.e02007_b37) 2020; 139 Deng (10.1016/j.sciaf.2023.e02007_b40) 2016; 6 10.1016/j.sciaf.2023.e02007_b51 10.1016/j.sciaf.2023.e02007_b52 Zeng (10.1016/j.sciaf.2023.e02007_b64) 2021; 10 Waljee (10.1016/j.sciaf.2023.e02007_b46) 2013; 3 10.1016/j.sciaf.2023.e02007_b25 Wang (10.1016/j.sciaf.2023.e02007_b54) 2005 Golub (10.1016/j.sciaf.2023.e02007_b33) 1979; 21 Brownlee (10.1016/j.sciaf.2023.e02007_b26) 2019; 21 Asiedu (10.1016/j.sciaf.2023.e02007_b14) 2021; 2021 Jonsson (10.1016/j.sciaf.2023.e02007_b59) 2002; 20 Asiedu (10.1016/j.sciaf.2023.e02007_b32) 2020; 2020 10.1016/j.sciaf.2023.e02007_b63 Hong (10.1016/j.sciaf.2023.e02007_b44) 2020; 20 Mukkamala (10.1016/j.sciaf.2023.e02007_b57) 2002 Cheon (10.1016/j.sciaf.2023.e02007_b3) 2009; 42 Golla (10.1016/j.sciaf.2023.e02007_b30) 2019 Adhinata (10.1016/j.sciaf.2023.e02007_b28) 2021; 7 Animasaun (10.1016/j.sciaf.2023.e02007_b15) 2022 Piccialli (10.1016/j.sciaf.2023.e02007_b20) 2021; 66 Sundararajan (10.1016/j.sciaf.2023.e02007_b23) 2018; 51 Tian (10.1016/j.sciaf.2023.e02007_b56) 2012; 18 Resche-Rigon (10.1016/j.sciaf.2023.e02007_b43) 2018; 27 Lahasan (10.1016/j.sciaf.2023.e02007_b7) 2019; 52 Shorten (10.1016/j.sciaf.2023.e02007_b49) 2019; 6 |
| References_xml | – volume: 2021 start-page: 1 year: 2021 end-page: 9 ident: b66 article-title: Recognition of augmented frontal face images using FFT-PCA/SVD algorithm publication-title: Appl. Comput. Intell. Soft Comput. – reference: F. Schroff, D. Kalenichenko, J. Philbin, Facenet: A unified embedding for face recognition and clustering, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 815–823. – year: 2022 ident: b15 article-title: Ratio of Momentum Diffusivity to Thermal Diffusivity: Introduction, Meta-Analysis, and Scrutinization – volume: 3 year: 2013 ident: b46 article-title: Comparison of imputation methods for missing laboratory data in medicine publication-title: BMJ Open – volume: 19 start-page: 4933 year: 2019 ident: b10 article-title: A convolutional neural network for impact detection and characterization of complex composite structures publication-title: Sensors – volume: 16 start-page: 62 year: 2022 ident: b60 article-title: An asymptotic expansion for the distribution of euclidean distance-based discriminant function in normal populations publication-title: J. Stat. Theory Pract. – reference: A.K. Singh, G.C. Nandi, Face recognition using facial symmetry, in: Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology, 2012, pp. 550–554. – year: 2017 ident: b17 article-title: Deep learning: a review – volume: 21 year: 2019 ident: b26 article-title: How to develop a face recognition system using FaceNet in keras publication-title: Mach. Learn. Mastery – volume: 11 start-page: 388 year: 2022 ident: b27 article-title: Implementation of FaceNet and support vector machine in a real-time web-based timekeeping application publication-title: IAES Int. J. Artif. Intell. – volume: 6 start-page: 21689 year: 2016 ident: b40 article-title: Multiple imputation for general missing data patterns in the presence of high-dimensional data publication-title: Sci. Rep. – volume: 34 year: 2022 ident: b21 article-title: Characterization of abnormalities in breast cancer images using nature-inspired metaheuristic optimized convolutional neural networks model publication-title: Concurr. Comput.: Pract. Exper. – volume: 88 start-page: 3588 year: 2018 end-page: 3619 ident: b47 article-title: A simulation comparison of imputation methods for quantitative data in the presence of multiple data patterns publication-title: J. Stat. Comput. Simul. – volume: 139 year: 2020 ident: b37 article-title: Spatial imputation for air pollutants data sets via low rank matrix completion algorithm publication-title: Environ. Int. – start-page: 1 year: 2023 end-page: 17 ident: b22 article-title: A multi-stage faster RCNN-based isplinception for skin disease classification using novel optimization publication-title: J. Digit. Imaging – volume: 179 start-page: 764 year: 2014 end-page: 774 ident: b48 article-title: Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study publication-title: Am. J. Epidemiol. – year: 2022 ident: b61 article-title: Photovoltaic single-diode model parametrization. An application to the calculus of the euclidean distance to an IV curve – reference: I. Kemelmacher-Shlizerman, S.M. Seitz, D. Miller, E. Brossard, The megaface benchmark: 1 million faces for recognition at scale, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 4873–4882. – start-page: 1 year: 2018 end-page: 6 ident: b16 article-title: A review of machine learning and deep learning applications publication-title: 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA) – start-page: 317 year: 2019 end-page: 325 ident: b30 article-title: Performance evaluation of facenet on low resolution face images publication-title: Communication, Networks and Computing: First International Conference, CNC 2018, Gwalior, India, March 22-24, 2018, Revised Selected Papers 1 – volume: 18 start-page: 5 year: 2012 end-page: 33 ident: b56 article-title: Recent advances on support vector machines research publication-title: Technol. Econ. Dev. Econ. – start-page: 1702 year: 2002 end-page: 1707 ident: b57 article-title: Intrusion detection using neural networks and support vector machines publication-title: Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN’02 (Cat. No. 02CH37290), Vol. 2 – volume: 179 start-page: 293 year: 2019 end-page: 294 ident: b19 article-title: Deep learning in medicine– promise, progress, and challenges publication-title: JAMA Internal Med. – year: 2005 ident: b54 article-title: Support Vector Machines: Theory and Applications, Vol. 177 – volume: 49 start-page: 3098 year: 2022 end-page: 3118 ident: b9 article-title: Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement publication-title: Eur. J. Nucl. Med. Mol. Imaging – volume: 2021 start-page: 1 year: 2021 end-page: 12 ident: b65 article-title: Assessing the performance of DWT-PCA/SVD face recognition algorithm under multiple constraints publication-title: J. Appl. Math. – volume: 66 start-page: 111 year: 2021 end-page: 137 ident: b20 article-title: A survey on deep learning in medicine: Why, how and when? publication-title: Inf. Fusion – volume: 7 start-page: 22 year: 2021 end-page: 30 ident: b28 article-title: Fatigue detection on face image using FaceNet algorithm and K-nearest neighbor classifier publication-title: J. Inf. Syst. Eng. Bus. Intell. – reference: G.B. Huang, M. Mattar, T. Berg, E. Learned-Miller, Labeled faces in the wild: A database forstudying face recognition in unconstrained environments, in: Workshop on Faces in‘Real-Life’Images: Detection, Alignment, and Recognition, 2008. – volume: 52 start-page: 2348 year: 2004 end-page: 2355 ident: b58 article-title: Applications of support vector machines to speech recognition publication-title: IEEE Trans. Signal Process. – volume: 2021 start-page: 1 year: 2021 end-page: 11 ident: b14 article-title: Assessing the effect of data augmentation on occluded frontal faces using DWT-PCA/SVD recognition algorithm publication-title: Adv. Multimed. – volume: 51 start-page: 1 year: 2018 end-page: 34 ident: b23 article-title: Deep learning for biometrics: A survey publication-title: ACM Comput. Surv. – volume: 6 start-page: 1 year: 2019 end-page: 48 ident: b49 article-title: A survey on image data augmentation for deep learning publication-title: J. Big Data – volume: 46 start-page: 1253 year: 2006 end-page: 1262 ident: b5 article-title: Quantifying facial expression recognition across viewing conditions publication-title: Vis. Res. – volume: 10 start-page: 1 year: 2017 end-page: 7 ident: b39 article-title: A comparison of multiple imputation methods for data with missing values publication-title: Indian J. Sci. Technol. – volume: 14 start-page: 1 year: 2014 end-page: 10 ident: b42 article-title: Joint modelling rationale for chained equations publication-title: BMC Med. Res. Methodol. – volume: 21 start-page: 215 year: 1979 end-page: 223 ident: b33 article-title: Generalized cross-validation as a method for choosing a good ridge parameter publication-title: Technometrics – year: 2018 ident: b1 article-title: Face recognition in low quality images: A survey – volume: 10 start-page: 581 year: 2021 end-page: 606 ident: b64 article-title: A survey of face recognition techniques under occlusion publication-title: IET Biom. – volume: 120 start-page: 106 year: 2013 end-page: 115 ident: b34 article-title: Comparison of five iterative imputation methods for multivariate classification publication-title: Chemometr. Intell. Lab. Syst. – volume: 27 start-page: 1634 year: 2018 end-page: 1649 ident: b43 article-title: Multiple imputation by chained equations for systematically and sporadically missing multilevel data publication-title: Stat. Methods Med. Res. – volume: 32 start-page: 4890 year: 2013 end-page: 4905 ident: b41 article-title: Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data publication-title: Stat. Med. – volume: 48 start-page: 598 year: 2013 end-page: 606 ident: b13 article-title: Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography publication-title: Invest. Radiol. – start-page: 1 year: 2019 end-page: 6 ident: b50 article-title: Face recognition using facenet (survey, performance test, and comparison) publication-title: 2019 Fourth International Conference on Informatics and Computing (ICIC) – start-page: 101 year: 2020 end-page: 121 ident: b55 article-title: Support vector machine publication-title: Machine Learning – volume: 39 start-page: 1156 year: 2020 end-page: 1166 ident: b38 article-title: A fair comparison of tree-based and parametric methods in multiple imputation by chained equations publication-title: Stat. Med. – volume: 85 year: 2020 ident: b4 article-title: A multi-scale three-dimensional face recognition approach with sparse representation-based classifier and fusion of local covariance descriptors publication-title: Comput. Electr. Eng. – volume: 12 start-page: 5195 year: 2022 ident: b62 article-title: Rough IPFCM clustering algorithm and its application on smart phones with euclidean distance publication-title: Appl. Sci. – volume: 2020 start-page: 1 year: 2020 end-page: 8 ident: b32 article-title: Recognition of reconstructed frontal face images using fft-pca/svd algorithm publication-title: J. Appl. Math. – reference: H. Chen, Y. Wang, T. Guo, C. Xu, Y. Deng, Z. Liu, S. Ma, C. Xu, C. Xu, W. Gao, Pre-trained image processing transformer, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 12299–12310. – start-page: 247 year: 2018 end-page: 251 ident: b35 article-title: Comparison of the most influential missing data imputation algorithms for healthcare publication-title: 2018 10th International Conference on Knowledge and Systems Engineering (KSE) – volume: 20 start-page: 1 year: 2020 end-page: 12 ident: b44 article-title: Accuracy of random-forest-based imputation of missing data in the presence of non-normality, non-linearity, and interaction publication-title: BMC Med. Res. Methodol. – year: 2010 ident: b31 article-title: Handbook of Image and Video Processing – volume: 28 start-page: 112 year: 2012 end-page: 118 ident: b45 article-title: MissForest– non-parametric missing value imputation for mixed-type data publication-title: Bioinformatics – volume: 1 start-page: 283 year: 2009 end-page: 289 ident: b53 article-title: Support vector machines publication-title: Wiley Interdiscip. Rev. Comput. Stat. – volume: 80 start-page: 899 year: 2018 end-page: 926 ident: b36 article-title: An imputation–regularized optimization algorithm for high dimensional missing data problems and beyond publication-title: J. R. Stat. Soc. Ser. B Stat. Methodol. – start-page: 495 year: 2020 end-page: 514 ident: b2 article-title: A comprehensive review on face recognition methods and factors affecting facial recognition accuracy publication-title: Proceedings of ICRIC 2019: Recent Innovations in Computing – volume: 52 start-page: 949 year: 2019 end-page: 979 ident: b7 article-title: A survey on techniques to handle face recognition challenges: occlusion, single sample per subject and expression publication-title: Artif. Intell. Rev. – volume: 45 start-page: 131 year: 2014 end-page: 136 ident: b12 article-title: Model-based iterative reconstruction: a promising algorithm for today’s computed tomography imaging publication-title: J. Med. Imaging Radiat. Sci. – start-page: 111 year: 2012 end-page: 118 ident: b6 article-title: Robust 3D face recognition in the presence of realistic occlusions publication-title: 2012 5th IAPR International Conference on Biometrics (ICB) – volume: 20 start-page: 369 year: 2002 end-page: 375 ident: b59 article-title: Support vector machines for face authentication publication-title: Image Vis. Comput. – volume: 2014 year: 2014 ident: b8 article-title: Efficient detection of occlusion prior to robust face recognition publication-title: Sci. World J. – start-page: 542 year: 2015 end-page: 546 ident: b24 article-title: Image recognition based on deep learning publication-title: 2015 Chinese Automation Congress (CAC) – volume: 27 start-page: 81 year: 2010 end-page: 89 ident: b11 article-title: Model-based image reconstruction for MRI publication-title: IEEE Signal Process. Mag. – start-page: 189 year: 2022 end-page: 202 ident: b29 article-title: Real-time masked face recognition using FaceNet and supervised machine learning publication-title: Proceedings of the 2nd International Conference on Electronics, Biomedical Engineering, and Health Informatics: ICEBEHI 2021, 3–4 November, Surabaya, Indonesia – volume: 42 start-page: 1340 year: 2009 end-page: 1350 ident: b3 article-title: Natural facial expression recognition using differential-AAM and manifold learning publication-title: Pattern Recognit. – year: 2005 ident: 10.1016/j.sciaf.2023.e02007_b54 – volume: 21 year: 2019 ident: 10.1016/j.sciaf.2023.e02007_b26 article-title: How to develop a face recognition system using FaceNet in keras publication-title: Mach. Learn. Mastery – volume: 18 start-page: 5 issue: 1 year: 2012 ident: 10.1016/j.sciaf.2023.e02007_b56 article-title: Recent advances on support vector machines research publication-title: Technol. Econ. Dev. Econ. doi: 10.3846/20294913.2012.661205 – volume: 120 start-page: 106 year: 2013 ident: 10.1016/j.sciaf.2023.e02007_b34 article-title: Comparison of five iterative imputation methods for multivariate classification publication-title: Chemometr. Intell. Lab. Syst. doi: 10.1016/j.chemolab.2012.11.010 – volume: 27 start-page: 81 issue: 4 year: 2010 ident: 10.1016/j.sciaf.2023.e02007_b11 article-title: Model-based image reconstruction for MRI publication-title: IEEE Signal Process. Mag. doi: 10.1109/MSP.2010.936726 – volume: 20 start-page: 1 issue: 1 year: 2020 ident: 10.1016/j.sciaf.2023.e02007_b44 article-title: Accuracy of random-forest-based imputation of missing data in the presence of non-normality, non-linearity, and interaction publication-title: BMC Med. Res. Methodol. doi: 10.1186/s12874-020-01080-1 – year: 2022 ident: 10.1016/j.sciaf.2023.e02007_b15 – volume: 2014 year: 2014 ident: 10.1016/j.sciaf.2023.e02007_b8 article-title: Efficient detection of occlusion prior to robust face recognition publication-title: Sci. World J. doi: 10.1155/2014/519158 – start-page: 1702 year: 2002 ident: 10.1016/j.sciaf.2023.e02007_b57 article-title: Intrusion detection using neural networks and support vector machines – volume: 42 start-page: 1340 issue: 7 year: 2009 ident: 10.1016/j.sciaf.2023.e02007_b3 article-title: Natural facial expression recognition using differential-AAM and manifold learning publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2008.10.010 – start-page: 1 year: 2023 ident: 10.1016/j.sciaf.2023.e02007_b22 article-title: A multi-stage faster RCNN-based isplinception for skin disease classification using novel optimization publication-title: J. Digit. Imaging – volume: 27 start-page: 1634 issue: 6 year: 2018 ident: 10.1016/j.sciaf.2023.e02007_b43 article-title: Multiple imputation by chained equations for systematically and sporadically missing multilevel data publication-title: Stat. Methods Med. Res. doi: 10.1177/0962280216666564 – volume: 2021 start-page: 1 year: 2021 ident: 10.1016/j.sciaf.2023.e02007_b65 article-title: Assessing the performance of DWT-PCA/SVD face recognition algorithm under multiple constraints publication-title: J. Appl. Math. doi: 10.1155/2021/7060270 – volume: 2021 start-page: 1 year: 2021 ident: 10.1016/j.sciaf.2023.e02007_b66 article-title: Recognition of augmented frontal face images using FFT-PCA/SVD algorithm publication-title: Appl. Comput. Intell. Soft Comput. – volume: 19 start-page: 4933 issue: 22 year: 2019 ident: 10.1016/j.sciaf.2023.e02007_b10 article-title: A convolutional neural network for impact detection and characterization of complex composite structures publication-title: Sensors doi: 10.3390/s19224933 – volume: 80 start-page: 899 issue: 5 year: 2018 ident: 10.1016/j.sciaf.2023.e02007_b36 article-title: An imputation–regularized optimization algorithm for high dimensional missing data problems and beyond publication-title: J. R. Stat. Soc. Ser. B Stat. Methodol. doi: 10.1111/rssb.12279 – volume: 49 start-page: 3098 issue: 9 year: 2022 ident: 10.1016/j.sciaf.2023.e02007_b9 article-title: Deep learning-based image reconstruction and post-processing methods in positron emission tomography for low-dose imaging and resolution enhancement publication-title: Eur. J. Nucl. Med. Mol. Imaging doi: 10.1007/s00259-022-05746-4 – volume: 34 issue: 4 year: 2022 ident: 10.1016/j.sciaf.2023.e02007_b21 article-title: Characterization of abnormalities in breast cancer images using nature-inspired metaheuristic optimized convolutional neural networks model publication-title: Concurr. Comput.: Pract. Exper. doi: 10.1002/cpe.6629 – start-page: 542 year: 2015 ident: 10.1016/j.sciaf.2023.e02007_b24 article-title: Image recognition based on deep learning – volume: 16 start-page: 62 issue: 4 year: 2022 ident: 10.1016/j.sciaf.2023.e02007_b60 article-title: An asymptotic expansion for the distribution of euclidean distance-based discriminant function in normal populations publication-title: J. Stat. Theory Pract. doi: 10.1007/s42519-022-00292-6 – volume: 10 start-page: 581 issue: 6 year: 2021 ident: 10.1016/j.sciaf.2023.e02007_b64 article-title: A survey of face recognition techniques under occlusion publication-title: IET Biom. doi: 10.1049/bme2.12029 – volume: 2020 start-page: 1 year: 2020 ident: 10.1016/j.sciaf.2023.e02007_b32 article-title: Recognition of reconstructed frontal face images using fft-pca/svd algorithm publication-title: J. Appl. Math. doi: 10.1155/2020/9127465 – volume: 7 start-page: 22 issue: 1 year: 2021 ident: 10.1016/j.sciaf.2023.e02007_b28 article-title: Fatigue detection on face image using FaceNet algorithm and K-nearest neighbor classifier publication-title: J. Inf. Syst. Eng. Bus. Intell. doi: 10.20473/jisebi.7.1.22-30 – volume: 6 start-page: 21689 issue: 1 year: 2016 ident: 10.1016/j.sciaf.2023.e02007_b40 article-title: Multiple imputation for general missing data patterns in the presence of high-dimensional data publication-title: Sci. Rep. doi: 10.1038/srep21689 – volume: 52 start-page: 949 year: 2019 ident: 10.1016/j.sciaf.2023.e02007_b7 article-title: A survey on techniques to handle face recognition challenges: occlusion, single sample per subject and expression publication-title: Artif. Intell. Rev. doi: 10.1007/s10462-017-9578-y – volume: 10 start-page: 1 issue: 19 year: 2017 ident: 10.1016/j.sciaf.2023.e02007_b39 article-title: A comparison of multiple imputation methods for data with missing values publication-title: Indian J. Sci. Technol. doi: 10.17485/ijst/2017/v10i19/110646 – volume: 39 start-page: 1156 issue: 8 year: 2020 ident: 10.1016/j.sciaf.2023.e02007_b38 article-title: A fair comparison of tree-based and parametric methods in multiple imputation by chained equations publication-title: Stat. Med. doi: 10.1002/sim.8468 – volume: 66 start-page: 111 year: 2021 ident: 10.1016/j.sciaf.2023.e02007_b20 article-title: A survey on deep learning in medicine: Why, how and when? publication-title: Inf. Fusion doi: 10.1016/j.inffus.2020.09.006 – ident: 10.1016/j.sciaf.2023.e02007_b51 – volume: 20 start-page: 369 issue: 5–6 year: 2002 ident: 10.1016/j.sciaf.2023.e02007_b59 article-title: Support vector machines for face authentication publication-title: Image Vis. Comput. doi: 10.1016/S0262-8856(02)00009-4 – year: 2010 ident: 10.1016/j.sciaf.2023.e02007_b31 – volume: 21 start-page: 215 issue: 2 year: 1979 ident: 10.1016/j.sciaf.2023.e02007_b33 article-title: Generalized cross-validation as a method for choosing a good ridge parameter publication-title: Technometrics doi: 10.1080/00401706.1979.10489751 – volume: 11 start-page: 388 issue: 1 year: 2022 ident: 10.1016/j.sciaf.2023.e02007_b27 article-title: Implementation of FaceNet and support vector machine in a real-time web-based timekeeping application publication-title: IAES Int. J. Artif. Intell. doi: 10.11591/ijai.v11.i1.pp388-396 – year: 2022 ident: 10.1016/j.sciaf.2023.e02007_b61 – ident: 10.1016/j.sciaf.2023.e02007_b25 doi: 10.1109/CVPR.2015.7298682 – volume: 3 issue: 8 year: 2013 ident: 10.1016/j.sciaf.2023.e02007_b46 article-title: Comparison of imputation methods for missing laboratory data in medicine publication-title: BMJ Open doi: 10.1136/bmjopen-2013-002847 – volume: 2021 start-page: 1 year: 2021 ident: 10.1016/j.sciaf.2023.e02007_b14 article-title: Assessing the effect of data augmentation on occluded frontal faces using DWT-PCA/SVD recognition algorithm publication-title: Adv. Multimed. doi: 10.1155/2021/4981394 – volume: 179 start-page: 764 issue: 6 year: 2014 ident: 10.1016/j.sciaf.2023.e02007_b48 article-title: Comparison of random forest and parametric imputation models for imputing missing data using MICE: a CALIBER study publication-title: Am. J. Epidemiol. doi: 10.1093/aje/kwt312 – year: 2018 ident: 10.1016/j.sciaf.2023.e02007_b1 – volume: 12 start-page: 5195 issue: 10 year: 2022 ident: 10.1016/j.sciaf.2023.e02007_b62 article-title: Rough IPFCM clustering algorithm and its application on smart phones with euclidean distance publication-title: Appl. Sci. doi: 10.3390/app12105195 – volume: 52 start-page: 2348 issue: 8 year: 2004 ident: 10.1016/j.sciaf.2023.e02007_b58 article-title: Applications of support vector machines to speech recognition publication-title: IEEE Trans. Signal Process. doi: 10.1109/TSP.2004.831018 – start-page: 111 year: 2012 ident: 10.1016/j.sciaf.2023.e02007_b6 article-title: Robust 3D face recognition in the presence of realistic occlusions – start-page: 247 year: 2018 ident: 10.1016/j.sciaf.2023.e02007_b35 article-title: Comparison of the most influential missing data imputation algorithms for healthcare – ident: 10.1016/j.sciaf.2023.e02007_b63 doi: 10.1145/2393216.2393308 – start-page: 189 year: 2022 ident: 10.1016/j.sciaf.2023.e02007_b29 article-title: Real-time masked face recognition using FaceNet and supervised machine learning – year: 2017 ident: 10.1016/j.sciaf.2023.e02007_b17 – volume: 85 year: 2020 ident: 10.1016/j.sciaf.2023.e02007_b4 article-title: A multi-scale three-dimensional face recognition approach with sparse representation-based classifier and fusion of local covariance descriptors publication-title: Comput. Electr. Eng. doi: 10.1016/j.compeleceng.2020.106700 – start-page: 495 year: 2020 ident: 10.1016/j.sciaf.2023.e02007_b2 article-title: A comprehensive review on face recognition methods and factors affecting facial recognition accuracy – volume: 51 start-page: 1 issue: 3 year: 2018 ident: 10.1016/j.sciaf.2023.e02007_b23 article-title: Deep learning for biometrics: A survey publication-title: ACM Comput. Surv. doi: 10.1145/3190618 – start-page: 1 year: 2018 ident: 10.1016/j.sciaf.2023.e02007_b16 article-title: A review of machine learning and deep learning applications – volume: 48 start-page: 598 issue: 8 year: 2013 ident: 10.1016/j.sciaf.2023.e02007_b13 article-title: Assessment of a model-based, iterative reconstruction algorithm (MBIR) regarding image quality and dose reduction in liver computed tomography publication-title: Invest. Radiol. doi: 10.1097/RLI.0b013e3182899104 – volume: 28 start-page: 112 issue: 1 year: 2012 ident: 10.1016/j.sciaf.2023.e02007_b45 article-title: MissForest– non-parametric missing value imputation for mixed-type data publication-title: Bioinformatics doi: 10.1093/bioinformatics/btr597 – volume: 6 start-page: 1 issue: 1 year: 2019 ident: 10.1016/j.sciaf.2023.e02007_b49 article-title: A survey on image data augmentation for deep learning publication-title: J. Big Data doi: 10.1186/s40537-019-0197-0 – volume: 46 start-page: 1253 issue: 8–9 year: 2006 ident: 10.1016/j.sciaf.2023.e02007_b5 article-title: Quantifying facial expression recognition across viewing conditions publication-title: Vis. Res. doi: 10.1016/j.visres.2005.10.028 – volume: 45 start-page: 131 issue: 2 year: 2014 ident: 10.1016/j.sciaf.2023.e02007_b12 article-title: Model-based iterative reconstruction: a promising algorithm for today’s computed tomography imaging publication-title: J. Med. Imaging Radiat. Sci. doi: 10.1016/j.jmir.2014.02.002 – ident: 10.1016/j.sciaf.2023.e02007_b18 doi: 10.1109/CVPR46437.2021.01212 – volume: 88 start-page: 3588 issue: 18 year: 2018 ident: 10.1016/j.sciaf.2023.e02007_b47 article-title: A simulation comparison of imputation methods for quantitative data in the presence of multiple data patterns publication-title: J. Stat. Comput. Simul. doi: 10.1080/00949655.2018.1530773 – volume: 179 start-page: 293 issue: 3 year: 2019 ident: 10.1016/j.sciaf.2023.e02007_b19 article-title: Deep learning in medicine– promise, progress, and challenges publication-title: JAMA Internal Med. doi: 10.1001/jamainternmed.2018.7117 – volume: 14 start-page: 1 year: 2014 ident: 10.1016/j.sciaf.2023.e02007_b42 article-title: Joint modelling rationale for chained equations publication-title: BMC Med. Res. Methodol. doi: 10.1186/1471-2288-14-28 – start-page: 317 year: 2019 ident: 10.1016/j.sciaf.2023.e02007_b30 article-title: Performance evaluation of facenet on low resolution face images – volume: 32 start-page: 4890 issue: 28 year: 2013 ident: 10.1016/j.sciaf.2023.e02007_b41 article-title: Multiple imputation for handling systematically missing confounders in meta-analysis of individual participant data publication-title: Stat. Med. doi: 10.1002/sim.5894 – ident: 10.1016/j.sciaf.2023.e02007_b52 doi: 10.1109/CVPR.2016.527 – start-page: 1 year: 2019 ident: 10.1016/j.sciaf.2023.e02007_b50 article-title: Face recognition using facenet (survey, performance test, and comparison) – volume: 139 year: 2020 ident: 10.1016/j.sciaf.2023.e02007_b37 article-title: Spatial imputation for air pollutants data sets via low rank matrix completion algorithm publication-title: Environ. Int. doi: 10.1016/j.envint.2020.105713 – volume: 1 start-page: 283 issue: 3 year: 2009 ident: 10.1016/j.sciaf.2023.e02007_b53 article-title: Support vector machines publication-title: Wiley Interdiscip. Rev. Comput. Stat. doi: 10.1002/wics.49 – start-page: 101 year: 2020 ident: 10.1016/j.sciaf.2023.e02007_b55 article-title: Support vector machine |
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