Applications of Artificial Intelligence in Ophthalmology: General Overview by Wei Lu, Yan Tong, Yue Yu, Yiqiao Xing, Changzheng Chen, Yin Shen

“…With the emergence of unmanned plane, autonomous vehicles, face recognition, and language processing, the artificial intelligence (AI) has remarkably revolutionized our lifestyle. …”
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Rolling Bearing Fault Diagnosis Based on STFT-Deep Learning and Sound Signals by Hongmei Liu, Lianfeng Li, Jian Ma

“…Stacked sparse autoencoders or other deep architectures have shown excellent performance in speech recognition, face recognition, text classification, image recognition, and other application domains. …”
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An MRI, SPECT and Neuropsychological Study of a Patient Presenting with Capgras Syndrome by J. Mackie, K. P. Ebmeier, R. E. O'Carroll

“…He demonstrated average or above average recognition memory for patterns, spaces or words, but exhibited a marked and disproportionate impairment in face recognition, performing at the 5th percentile. In addition he demonstrated markedly impaired performance on various tests of executive function. …”
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Searching, Navigating, and Recommending Movies through Emotions: A Scoping Review by Nuno Piçarra, Eduardo Reis, Teresa Chambel, Patrícia Arriaga

“…Sentiment analysis (n=31) is frequently used for emotion identification, followed by subjective evaluations (n=15), movie low-level audio and visual features (n = 11), and face recognition technologies (n=8). We discuss limitations and offer a brief review of current emotion models and research.…”
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Deep patch‐wise supervision for presentation attack detection by Alperen Kantarcı, Hasan Dertli, Hazım Kemal Ekenel

“…Abstract Face recognition systems have been widely deployed in various applications, such as online banking and mobile payment. …”
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The Role of Artificial Intelligence in Providing People With Privacy: Survey by Salar Raees, Mohammed Al-Tamimi

“…The task at hand is assessing various face recognition and identification tools and algorithms, with a specific emphasis on those that exhibit superior accuracy and efficiency in presenting outcomes. …”
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A Three-Dimensional Anisotropic Diffusion Equation-Based Video Recognition Model for Classroom Concentration Evaluation in English Language Teaching by Yanghong Liu, Jintao Liu

“…Based on the above face detection and expression recognition algorithms, the classroom concentration analysis system based on expression recognition is designed to achieve real-time acquisition and processing of classroom images, complete student classroom attendance records using face detection and face recognition methods, and analyze students’ concentration from the face integrity and facial expression of students facing the blackboard by combining face detection and expression recognition to visualize and display students’ classroom data for teachers, students, and parents with more data support and help.…”
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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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Lip forgery detection via spatial-frequency domain combination by Jiaying LIN, Wenbo ZHOU, Weiming ZHANG, Nenghai YU

“…In recent years, numerous “face-swapping” videos have emerged in social networks, one of the representatives is the lip forgery with speakers.While making life more entertaining for the public, it poses a significant crisis for personal privacy and property security in cyberspace.Currently, under non-destructive conditions, most of the lip forgery detection methods achieve good performance.However, the compression operations are widely used in practice especially in social media platforms, face recognition and other scenarios.While saving pixel and time redundancy, the compression operations affect the video quality and destroy the coherent integrity of pixel-to-pixel and frame-to-frame in the spatial domain, and then the degradation of its detection performance and even misjudgment of the real video will be caused.When the information in the spatial domain cannot provide sufficiently effective features, the information in the frequency domain naturally becomes a priority research object because it can resist compression interference.Aiming at this problem, the advantages of frequency information in image structure and gradient feedback were analyzed.Then the lip forgery detection via spatial-frequency domain combination was proposed, which effectively utilized the corresponding characteristics of information in spatial and frequency domains.For lip features in the spatial domain, an adaptive extraction network and a light-weight attention module were designed.For frequency features in the frequency domain, separate extraction and fusion modules for different components were designed.Subsequently, by conducting a weighted fusion of lip features in spatial domain and frequency features in frequency domain, more texture information was preserved.In addition, fine-grained constraints were designed during the training to separate the inter-class distance of real and fake lip features while closing the intra-class distance.Experimental results show that, benefiting from the frequency information, the proposed method can enhance the detection accuracy under compression situation with certain transferability.On the other hand, in the ablation study conducted on the core modules, the results verify the effectiveness of the frequency component for anti-compression and the constraint of the dual loss function in training.…”
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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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BDC-DAL: A new algorithm using blueprint difference convolution and dual auxiliary supervision for lightweight face anti-spoofing(BDC-DAL：基于蓝图差分卷积和双重辅助监督的轻量化人脸活体检测算法)... by 叶继华(YE Jihua), 梁芳昕(LIANG Fangxin), 王超(WANG Chao), 肖顺杰(XIAO Shunjie), 宗义(ZONG Yi), 江爱文(JIANG Aiwen)

“…Face anti-spoofing is an integral part of securing face recognition systems. Most current face anti-spoofing methods employ deep convolutional neural networks, and although these systems can provide excellent detection performance, they often involve large number of parameters and computational complexity, which limits their application on resource-limited devices. …”
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Self /other recognition and distinction in adolescents with anorexia nervosa: A pilot study using a double mirror paradigm. by Nathalie Lavenne-Collot, Emilie Maubant, Stéphanie Déroulez, Guillaume Bronsard, Moritz Wehrmann, Michel Botbol, Alain Berthoz

“…<h4>Conclusions</h4>Although additional research is needed to replicate the results of this pilot study, it revealed the first behavioural evidence of altered SOD in individuals affected by anorexia nervosa through an embodied, semiecological face-recognition paradigm. The relationships between anomalies in body perception and alterations in interpersonal relationships are discussed within an integrative framework from phenomenology to neuroscience, and new research and therapeutic perspectives are presented.…”
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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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