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Visual Informatics 2023年第1期7卷 1-17页

作者： Waleed Maqableh Faisal Y.Alzyoud Jamal Zraqou Luminus Technical University College SAE Amman InstituteAmmanJordan Isra University AmmanJordan University of Petra AmmanJordan

Digital learning is becoming increasingly important in the crisis COVID-19 and is widespread in most *** proliferation of smart devices and 5G telecommunications systems are contributing to the development of digital learning systems as an alternative to traditional learning *** learning includes blended learning,online learning,and personalized learning which mainly depends on the use of new technologies and strategies,so digital learning is widely developed to improve education and combat emerging disasters such as COVID-19 *** the tremendous benefits of digital learning,there are many obstacles related to the lack of digitized curriculum and collaboration between teachers and ***,many attempts have been made to improve the learning outcomes through the following strategies:collaboration,teacher convenience,personalized learning,cost and time savings through professional development,and *** this study,facial expressions and heart rates are used to measure the effectiveness of digital learning systems and the level of learners’engagement in learning *** results showed that the proposed approach outperformed the known related works in terms of learning *** results of this research can be used to develop a digital learning environment.

关键词： E-learning COVID-19 Face-to-face learning facial expressions Heart pulse

The Application of facial expressions in English Classroom Teaching——A Study on Stuednts from Yunnan Posts and Telecommunications School

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校园英语(教研版) 2012年第1期 118-118页

作者：刘家云云南省邮电学校

A facial exprsession is one of body languages,which plays a very important role in our English classroom *** to complicated classification of body languange,this paper merely chooses facial expressions to discuss,and ... 详细信息

关键词： facial expressions body language application

EEG Mapping of Cortical Activation Related to Emotional Stroop with facial expressions: A TREFACE Study

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Journal of Behavioral and Brain Science 2022年第10期12卷 514-532页

作者： Edward Prada Maria C. H. Tavares Ana Garcia Corina Satler Lia Martinez Cândida H. L. Alves Carlos Tomaz Laboratory of Neurosciences and Behavior Department of Physiological Sciences University of Bras&iacute lia Bras&iacute lia Brazil Faculty of Psychology Social Sciences Department Universidad Pontificia Bolivariana Seccional Bucaramanga Bucaramanga Colombia University of Brasí lia Ceilandia Campus Bras&iacute lia Brazil Department of Psychology Federal University of Maranh&atilde o S&atilde o Luí s Brazil Laboratory of Neurosciences and Behavior Master’s Program in Environment CEUMA University S&atilde o Luis Brazil

TREFACE (Test for Recognition of facial expressions with Emotional Conflict) is a computerized model for investigating the emotional factor in executive functions based on the Stroop paradigm, for the recognition of emotional expressions in human faces. To investigate the influence of the emotional component at the cortical level, the electroencephalographic (EEG) recording technique was used to measure the involvement of cortical areas during the execution of certain tasks. Thirty Brazilian native Portuguese-speaking graduate students were evaluated on their anxiety and depression levels and on their well-being at the time of the session. The EEG recording was performed in 19 channels during the execution of the TREFACE test in the 3 stages established by the model-guided training, reading, and recognition—both with congruent conditions, when the image corresponds to the word shown, and incongruent condition, when there is no correspondence. The results showed better performance in the reading stage and in congruent conditions, while greater intensity of cortical activation in the recognition stage and in incongruent conditions. In a complementary way, specific frontal activations were observed: intense theta frequency activation in the left extension representing the frontal recruitment of posterior regions in information processing;also, activation in alpha frequency in the right frontotemporal line, illustrating the executive processing in the control of attention, in addition to the dorsal manifestation of the prefrontal side, for emotional performance. Activations in beta and gamma frequencies were displayed in a more intensely distributed way in the recognition stage. The results of this mapping of cortical activity in our study can help to understand how words and images of faces can be regulated in everyday life and in clinical contexts, suggesting an integrated model that includes the neural bases of the regulation strategy.

关键词： EEG Emotion facial expressions Executive Functions Stroop TREFACE

A Modified CNN Network for Automatic Pain Identification Using facial expressions

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Journal of Software Engineering and Applications 2021年第8期14卷 400-417页

作者： Ioannis Karamitsos IIham Seladji Sanjay Modak Rochester Institute of Technology Dubai UAE

Pain is a strong symptom of diseases. Being an involuntary unpleasant feeling, it can be considered a reliable indicator of health issues. Pain has always been expressed verbally, but in some cases, traditional patient self-reporting is not efficient. On one side, there are patients who have neurological disorders and cannot express themselves accurately, as well as patients who suddenly lose consciousness due to an abrupt faintness. On another side, medical staff working in crowded hospitals need to focus on emergencies and would opt for the automation of the task of looking after hospitalized patients during their entire stay, in order to notice any pain-related emergency. These issues can be tackled with deep learning. Knowing that pain is generally followed by spontaneous facial behaviors, facial expressions can be used as a substitute to verbal reporting, to express pain. In this paper, a convolutional neural network (CNN) model was built and trained to detect pain through patients’ facial expressions, using the UNBC-McMaster Shoulder Pain dataset. First, faces were detected from images using the Haarcascade Frontal Face Detector provided by OpenCV, and preprocessed through gray scaling, histogram equalization, face detection, image cropping, mean filtering, and normalization. Next, preprocessed images were fed into a CNN model which was built based on a modified version of the VGG16 architecture. The model was finally evaluated and fine-tuned in a continuous way based on its accuracy, which reached 92.5%.

关键词： CNN Computer Vision facial expressions Image Processing Pain Assessment

On the Importance of Bodily Gestures,facial expressions,and Intonations to Thinking Expression and Interpretation

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海外英语 2021年第17期 288-289页

作者：石桐蒋翃遐兰州大学外国语学院

Bodily gestures,facial expressions,and intonations are argued to be notably important features of spoken languagewhich are opposed to written *** gestures with or without spoken words can influence the clarity and density of expres-sion and involvement of *** expressions whether or not correspond with exact thought could be"decoded"to influencethe extent of intelligibility of *** can always reflect the mutual beliefs concerning the propositional content andstates of consciousness relating to the expression and ***,these can considerably improve or abate the accura-cy of expression and interpretation of thought.

关键词： Bodily gestures facial expressions intonations thought

Robust Face Recognition Against expressions and Partial Occlusions

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International Journal of Automation and computing 2016年第4期13卷 319-337页

作者： Fadhlan Kamaru Zaman Amir Akramin Shafie Yasir Mohd Mustafah Faculty of Electrical Engineering Universiti Teknologi MARA Shah Alam 40450 Selangor Malaysia Department of Mechatronics Engineering International Islamic University Malaysia Kuala Lumpur 50728 Malaysia

facial features under variant-expressions and partial occlusions could have degrading effect on overall face recognition performance. As a solution, we suggest that the contribution of these features on final classification should be determined. In order to represent facial features＇ contribution according to their variations, we propose a feature selection process that describes facial features as local independent component analysis （ICA） features. These local features are acquired using locally lateral subspace （LLS） strategy. Then, through linear discriminant analysis （LDA） we investigate the intraclass and interclass representation of each local ICA feature and express each feature＇s contribution via a weighting process. Using these weights, we define the contribution of each feature at local classifier level. In order to recognize faces under single sample constraint, we implement LLS strategy on locally linear embedding （LLE） along with the proposed feature selection. Additionally, we highlight the efficiency of the implementation of LLS strategy. The overall accuracy achieved by our approach on datasets with different facial expressions and partial occlusions such as AR, JAFFE, FERET and CK% is 90.70%. We present together in this paper survey results on face recognition performance and physiological feature selection performed by human subjects.

关键词： Face recognition facial expressions dimensionality reduction single sample feature selection.

Secure Rotation Invariant Face Detection System for Authentication

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Computers, Materials & Continua 2022年第1期70卷 1955-1974页

作者： Amit Verma Mohammed Baljon Shailendra Mishra Iqbaldeep Kaur Ritika Saini Sharad Saxena Sanjay Kumar Sharma Department of Computer Science&Engineering Chandigarh Group of CollegesMohali140317India Department of Computer Engineering College of Computer&Information ScienceMajmaah University11952Saudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering&TechnologyPatiala147004India Department of Computer Centre&Campus Network Facility Science Complex PO Central UniversityGachibowliHyderabad500046TelanganaIndia

Biometric applications widely use the face as a component for recognition and automatic *** rotation is a variable component and makes face detection a complex and challenging task with varied angles and *** problem has been investigated,and a novice algorithm,namely RIFDS(Rotation Invariant Face Detection System),has been *** objective of the paper is to implement a robust method for face detection taken at various *** to achieve better results than known algorithms for face *** RIFDS Polar Harmonic Transforms(PHT)technique is combined with Multi-Block Local Binary Pattern(MBLBP)in a hybrid *** MBLBP is used to extract texture patterns from the digital image,and the PHT is used to manage invariant rotation *** this manner,RIFDS can detect human faces at different rotations and with different facial *** RIFDS performance is validated on different face databases like LFW,ORL,CMU,MIT-CBCL,JAFFF Face Databases,and Lena *** results show that the RIFDS algorithm can detect faces at varying angles and at different image resolutions and with an accuracy of 99.9%.The RIFDS algorithm outperforms previous methods like Viola-Jones,Multi-blockLocal Binary Pattern(MBLBP),and Polar HarmonicTransforms(PHTs).The RIFDS approach has a further scope with a genetic algorithm to detect faces(approximation)even from shadows.

关键词： Pose variations face detection frontal faces facial expressions emotions

Data Mining Approach Based on Hierarchical Gaussian Mixture Representation Model

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Intelligent Automation & Soft Computing 2023年第3期35卷 3727-3741页

作者： Hanan A.Hosni Mahmoud Alaaeldin M.Hafez Fahd Althukair Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia Department of Electrical Engineering and Computer Sciences College of EngineeringUniversity of CaliforniaBerkeleyUSA

Inﬁnite Gaussian mixture process is a model that computes the Gaus-sian mixture parameters with *** process is a probability density distribu-tion with adequate training data that can converge to the input density *** this paper,we propose a data mining model namely Beta hierarchical distribution that can solve axial data modeling.A novel hierarchical Two-Hyper-Parameter Poisson stochastic process is developed to solve grouped data *** solution uses data mining techniques to link datum in groups by linking their *** learning techniques are novel presentations of Gaussian model-ling that use prior knowledge of the representation hyper-parameters and approx-imate them in a closed *** are performed on axial data modeling of Arabic Script classiﬁcation and depict the effectiveness of the proposed method using a hand written benchmark dataset which contains complex handwritten Ara-bic *** are also performed on the application of facial expres-sion recognition and prove the accuracy of the proposed method using a benchmark dataset which contains eight different facial expressions.

关键词： Data classiﬁcation handwritten Arabic classiﬁcation facial expressions

Robust facial expression recognition system in higher poses

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Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 159-173页

作者： Ebenezer Owusu Justice Kwame Appati Percy Okae Department of Computer Science University of GhanaP.O.Box LG 163AccraGhana Department of Computer Engineering University of GhanaP.O.Box LG 77AccraGhana

facial expression recognition(FER)has numerous applications in computer security,neuroscience,psychology,and *** to its non-intrusiveness,it is considered a useful technology for combating ***,FER is plagued with several challenges,the most serious of which is its poor prediction accuracy in severe head *** aim of this study,therefore,is to improve the recognition accuracy in severe head poses by proposing a robust 3D head-tracking algorithm based on an ellipsoidal model,advanced ensemble of AdaBoost,and saturated vector machine(SVM).The FER features are tracked from one frame to the next using the ellipsoidal tracking model,and the visible expressive facial key points are extracted using Gabor *** ensemble algorithm(Ada-AdaSVM)is then used for feature selection and *** proposed technique is evaluated using the Bosphorus,BU-3DFE,MMI,CK^(+),and BP4D-Spontaneous facial expression *** overall performance is outstanding.

关键词： facial expressions Three-dimensional head pose Ellipsoidal model Gabor filters Ada-AdaSVM

Semantic Knowledge based on Fuzzy System for Describing facial Expression 36

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Semantic Knowledge based on Fuzzy System for Describing Faci...