Driver identification and fatigue detection algorithm based on deep learning by Yuhua Ma, Ye Tao, Yuandan Gong, Wenhua Cui, Bo Wang

“…Firstly, this paper studies the detection algorithms of driver fatigue at home and abroad, and analyzes the advantages and disadvantages of the existing algorithms. Secondly, a face recognition module is introduced to crop and align the acquired faces and input them into the Facenet network model for feature extraction, thus completing the identification of drivers. …”
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Data pre-processing to increase the quality of optical text recognition systems by Konstantin Dergachov, Leonid Krasnov, Vladislav Bilozerskyi, Anatoly Zymovin

“…A package of algorithms for preliminary processing of photographs of documentation has been created, in which, to increase the functionality of data identification, a face detection algorithm is also built in, intended for their further recognition (face recognition). A number of service procedures are provided to ensure the convenience of data processing and their information protection. …”
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Enhanced Deep Learning Architectures for Face Liveness Detection for Static and Video Sequences by Ranjana Koshy, Ausif Mahmood

“…Face liveness detection is a critical preprocessing step in face recognition for avoiding face spoofing attacks, where an impostor can impersonate a valid user for authentication. …”
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Assessment and Estimation of Face Detection Performance Based on Deep Learning for Forensic Applications by Deisy Chaves, Eduardo Fidalgo, Enrique Alegre, Rocío Alaiz-Rodríguez, Francisco Jáñez-Martino, George Azzopardi

“…Face recognition is a valuable forensic tool for criminal investigators since it certainly helps in identifying individuals in scenarios of criminal activity like fugitives or child sexual abuse. …”
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Classification of Alzheimer's Disease, Mild Cognitive Impairment, and Cognitively Unimpaired Individuals Using Multi-feature Kernel Discriminant Dictionary Learning by Qing Li, Xia Wu, Xia Wu, Lele Xu, Kewei Chen, Li Yao, Li Yao, Alzheimer's Disease Neuroimaging Initiative

“…The current study focused on distinguishing AD or MCI from CU based on the multi-feature kernel supervised within-Class-similar discriminative dictionary learning algorithm (MKSCDDL), which we introduced in a previous study, demonstrating that MKSCDDL had superior performance in face recognition. Structural magnetic resonance imaging (sMRI), fluorodeoxyglucose (FDG) positron emission tomography (PET), and florbetapir-PET data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were all included for classification of AD vs. …”
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Ethical Concerns While Using Artificial Intelligence in Recruitment of Employees by Aashima Gupta, Mridula Mishra

“…In recent years, many companies have used various Artificial Intelligence tools such as chatbots and face recognition software for fulfilling their hiring needs. …”
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Biometric Performance as a Function of Gallery Size by Lee Friedman, Hal Stern, Vladyslav Prokopenko, Shagen Djanian, Henry Griffith, Oleg Komogortsev

“…We studied these phenomena with synthetic data as well as real data from a face recognition study. It is well known that the Rank-1 IR declines with increasing gallery size, and that the relationship is linear against log(gallery size). …”
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Overestimation of eye size: People see themselves with bigger eyes in a holistic approach by Kyoko Hine, Hikaru Okubo

“…A face contains crucial information for identification; moreover, face recognition is superior to other types of recognition. …”
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Fine-Tuning of Pre-Trained Deep Face Sketch Models Using Smart Switching Slime Mold Algorithm by Khaled Mohammad Alhashash, Hussein Samma, Shahrel Azmin Suandi

“…There are many pre-trained deep learning-based face recognition models developed in the literature, such as FaceNet, ArcFace, VGG-Face, and DeepFace. …”
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Image Similarity Searching Use Multi Part Cutting And Grayscale Color Histogram by Sofyan Pariyasto, Kusrini, Hanif Al Fatta

“…Dalam bidang pendidikan computer vision dapat dimaanfaat untuk proses absen otomatis memlaui face recognition, dalam hal retail bisa dimanfaatkan untuk proses sorting melalui object detection. …”
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Emotional declarative memory assessment of patients with mesial temporal lobe epilepsy and patients submitted to mesial temporal lobectomy Avaliação da memória declarativa emociona... by Lara De Vecchi Machado, Jean Edith Frank, Carlos Tomaz

“…The main objective of this work was to investigate neurocognitive function, especially the emotional working memory of patients with unilateral mesial temporal lobe epilepsy, and that of patients submitted to unilateral mesial temporal lobectomy. A face recognition test that can simultaneously recruit the frontal lobe (working memory) and mesial temporal lobe (emotional memory) was used to investigate emotional working memory. …”
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A Novel Deep Learning Architecture With Image Diffusion for Robust Face Presentation Attack Detection by Madini O. Alassafi, Muhammad Sohail Ibrahim, Imran Naseem, Rayed AlGhamdi, Reem Alotaibi, Faris A. Kateb, Hadi Mohsen Oqaibi, Abdulrahman A. Alshdadi, Syed Adnan Yusuf

“…Face presentation attack detection (PAD) is considered to be an essential and critical step in modern face recognition systems. Face PAD aims at exposing an imposter or an unauthorized person seeking to deceive the authentication system. …”
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Система виявлення обличчя на зображенні з використанням глибинної згорткової нейронної мережі by О. В. Яловега, Р. А. Мельник

“…Вирішено використати набір даних LFW – People (Face Recognition) для навчання моделі. Використано Python бібліотеку LabelImg, щоб попередньо промаркувати навчальні дані, які нейронна мережа повинна знаходити на зображенні. …”
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Smart Classroom Monitoring Using Novel Real-Time Facial Expression Recognition System by Shariqa Fakhar, Junaid Baber, Sibghat Ullah Bazai, Shah Marjan, Michal Jasinski, Elzbieta Jasinska, Muhammad Umar Chaudhry, Zbigniew Leonowicz, Shumaila Hussain

“…The proposed novel facial features for each emotion are initially detected using HOG for face recognition, and automatic emotion recognition is then performed by training a convolutional neural network (CNN) that takes real-time input from a camera deployed in the classroom. …”
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A Decision Support System for Face Sketch Synthesis Using Deep Learning and Artificial Intelligence by Irfan Azhar, Muhammad Sharif, Mudassar Raza, Muhammad Attique Khan, Hwan-Seung Yong

“…Results of this modified U-Net are acquired by the legacy NLDA (1998) scheme of face recognition and its newer version, OpenBR (2013), which demonstrate an improvement of 5% compared with the current state of the art in its relevant domain.…”
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Face Liveness Detection Using Dynamic Local Ternary Pattern (DLTP) by Sajida Parveen, Sharifah Mumtazah Syed Ahmad, Nidaa Hasan Abbas, Wan Azizun Wan Adnan, Marsyita Hanafi, Nadeem Naeem

“…Face spoofing is considered to be one of the prominent threats to face recognition systems. However, in order to improve the security measures of such biometric systems against deliberate spoof attacks, liveness detection has received significant recent attention from researchers. …”
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The ‘Narcissus Effect’: Top-down alpha-beta band modulation of face-related brain areas during self-face processing by Elisabet Alzueta, María Melcón, Ole Jensen, Almudena Capilla

“…Critically, source analysis showed that this activity was generated in key brain regions for self-face recognition, such as the fusiform gyrus. As in the Myth of Narcissus, our results indicate that one’s own face might have the potential to hijack attention. …”
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AdaBoost Algorithm in Trustworthy Network for Anomaly Intrusion Detection by Guo Wei, Luo Zhenyu, Chen Hexiong, Hang Feilu, Zhang Jun, Al Bayatti Hilal

“…With remarkable usability and effectiveness, AdaBoost algorithm has been widely used in many fields, such as face recognition, speech enhancement, natural language processing, and network intrusion detection. …”
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Fine-Grained Facial Expression Recognition in Multiple Smiles by Zhijia Jin, Xiaolu Zhang, Jie Wang, Xiaolin Xu, Jiangjian Xiao

“…We propose Smile Transformer, a network architecture for FER based on the Swin Transformer, to enhance the local perception capability of the model and improve the accuracy of fine-grained face recognition. Moreover, a convolutional block attention module (CBAM) was designed, to focus on important features of the face image and suppress unnecessary regional responses. …”
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A Survey on Deep Learning in COVID-19 Diagnosis by Xue Han, Zuojin Hu, Shuihua Wang, Yudong Zhang

“…The convolutional neural network (CNN) is very popular in computer vision applications, such as applied to biological image segmentation, traffic sign recognition, face recognition, and other fields. It is one of the most widely used machine learning methods. …”
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