ALGORITHM OF PREPARATION OF THE TRAINING SAMPLE USING 3D-FACE MODELING by D. I. Samal, I. I. Frolov

“…The preparation and preliminary processing of images contains the following constituents like detection and localization of area of the person on the image, assessment of an angle of rotation and an inclination, extension of the range of brightness of pixels and an equalization of the histogram to smooth the brightness and contrast characteristics of the processed images, scaling of the localized and processed area of the person, creation of a vector of features of the scaled and processed image of the person by a Principal component analysis (algorithm NIPALS), training of the multiclass SVM-classifier.The provided algorithm of expansion of the training selection is oriented to be used in practice and allows to expand using 3D-models the processed range of 2D – photographs of persons that positively affects results of identification in system of face recognition. This approach allows to compensate in a certain measure a lack of initial images for identification improvement of quality.…”
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Unveiling the content of frontal feedback in challenging object recognition by Nastaran Darjani, Jalaledin Noroozi, Mohammad-Reza A. Dehaqani

“…Our findings elucidate the critical role of frontal feedback in the late processing stage of occluded face recognition, contributing to enhanced accuracy in identification. …”
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Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization by Mohammed Hasan Abdulameer, Siti Norul Huda Sheikh Abdullah, Zulaiha Ali Othman

“…Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. …”
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Face super-resolution via iterative collaboration between multi-attention mechanism and landmark estimation by Chang-Teng Shi, Meng-Jun Li, Zhi Yong An

“…Abstract Face super-resolution technology can significantly enhance the resolution and quality of face images, which is crucial for applications such as surveillance, forensics, and face recognition. However, existing methods often fail to fully utilize multi-scale information and facial priors, resulting in poor recovery of facial structures in complex images. …”
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Face morphing attacks and face image quality: The effect of morphing and the unsupervised attack detection by quality by Biying Fu, Naser Damer

“…The authors theorise that the morphing processes might have an effect on both, the perceptual image quality and the image utility in face recognition (FR) when compared to bona fide samples. …”
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Research on Mental Health Monitoring Scheme of Migrant Children Based on Convolutional Neural Network Based on Deep Learning by Guangyan Yang

“…This paper studies children’s smiling face recognition based on deep neural network. In order to obtain a better identification effect of mental health problems of children, this paper attempts to use multisource data, including consumption data, access control data, network logs, and grade data, and proposes a multisource data-based mental health problem identification algorithm. …”
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Beyond minutiae: inferring missing details from global structure in fingerprints by Rachel A. Searston, Matthew B. Thompson, Samuel G. Robson, Jason M. Tangen

“…These results align with prior research on perceptual expertise in other expert domains, such as radiology, and extend our understanding of scene and face recognition to fingerprint examination. Our findings show that expertise emerges from an ability to combine local and global visual information—experts skillfully process both the fine details and overall patterns in fingerprints. …”
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Learning deep forest for face anti-spoofing: An alternative to the neural network against adversarial attacks by Rizhao Cai, Liepiao Zhang, Changsheng Chen, Yongjian Hu, Alex Kot

“…Face anti-spoofing (FAS) is significant for the security of face recognition systems. neural networks (NNs), including convolutional neural network (CNN) and vision transformer (ViT), have been dominating the field of the FAS. …”
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Tracking illegal activities using video surveillance systems: a review of the current state of research by D. O. Zhadan, M. V. Mordvyntsev, D. V. Pashniev

“…The methods of detecting illegal actions, weapons, face recognition and traffic violations using video surveillance cameras are analysed. …”
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Apply IOT technology to practice a pandemic prevention body temperature measurement system: A case study of response measures for COVID-19 by Wei-Ling Lin, Chun-Hung Hsieh, Tung-Shou Chen, Jeanne Chen, Jian-Le Lee, Wei-Chung Chen

“…The cost of fast-checking body temperature measurement equipment, such as infrared body temperature detection and face recognition temperature machine, is too high, and it is difficult to build Disease Surveillance System (DSS). …”
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Face Boundary Formulation for Harmonic Models: Face Image Resembling by Hung-Tsai Huang, Zi-Cai Li, Yimin Wei, Ching Yee Suen

“…The formulation of the face boundary is imperative for face recognition, transformation, and combination. Mapping between the source and target face boundaries with constituent pixels is explored by two approaches: cubic spline interpolation and ordinary differential equation (ODE) using Hermite interpolation. …”
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Application Of ArtifiCial Intelligence in E-Governance: A Comparative Study of Supervised Machine Learning and Ensemble Learning Algorithms on Crime Prediction. by Niyonzima, Ivan, Muhaise, Hussein, Akankwasa, Aureri

“…Machine learning, a subfield of artificial intelligence, has been used by government agencies in developed countries in different operations like face recognition, computer forensics, image and video analysis to identify criminals and crime predictions. …”
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