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facial features of an Air Gun Array Wavelet in the Time-Frequency Domain Based on Marine Vertical Cables

Journal of Ocean University of China 2021年第6期20卷 1371-1382页

作者： ZHANG Dong LIU Huaishan XING Lei WEI Jia WANG Jianhua ZHOU Heng GE Xinmin Key Laboratory of Submarine Geosciences and Prospecting Techniques Ministry of EducationCollege of Marine GeosciencesOcean University of ChinaQingdao 266100China Qingdao Institute of Marine Geology China Geological SurveyMinistry of Natural ResourcesQingdao 266071China Evaluation and Detection Technology Laboratory of Marine Mineral Resources Qingdao National Laboratory for Marine Scienceand TechnologyQingdao 266071China National Engineering Laboratory of Offshore Oil Exploration CNOOC Research InstituteBeijing 100028China BGP International CNPCZhuozhou 072750China School of Geosciences China University of Petroleum(East China)Qingdao 266580China

Air gun arrays are often used in marine energy exploration and marine geological *** study of the single bubble dynamics and multibubbles produced by air guns interacting with each other is helpful in understanding pressure *** used the van der Waals air gun model to simulate the wavelets of a sleeve gun of various offsets and arrival *** factors were taken into account,such as heat transfer,the thermodynamically open quasi-static system,the vertical rise of the bubble,and air gun post *** vertical cables are located on the seafloor,but hydrophones are located in seawater and are far away from the air gun array *** situation conforms to the acquisition conditions of the air gun far-field wavelet and thus avoids the problems of ship noise,ocean surges,and ***-quality 3D wavelet data of air gun arrays were collected during a vertical cable test in the South China Sea in *** proposed an evaluation method of multidimensional facial features,including zeropeak amplitude,peak-peak amplitude,bubble period,primary-to-bubble ratio,frequency spectrum,instantaneous amplitude,instantaneous phase,and instantaneous frequency,to characterize the 3D air gun wave *** match between the facial features in the field and simulated data provides confidence for the use of the van der Waals air gun model to predict air gun wavelet and facial features to evaluate air gun array.

关键词： air gun van der Waals marine vertical cable facial features multidimensional

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Deepfake Video Detection Employing Human facial features

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Journal of Computer and Communications 2023年第12期11卷 1-13页

作者： Daniel Schilling Weiss Nguyen Desmond T. Ademiluyi Computer Science (DSCS) Aspen University Phoenix USA

Deepfake technology can be used to replace people’s faces in videos or pictures to show them saying or doing things they never said or did. Deepfake media are often used to extort, defame, and manipulate public opinion. However, despite deepfake technology’s risks, current deepfake detection methods lack generalization and are inconsistent when applied to unknown videos, i.e., videos on which they have not been trained. The purpose of this study is to develop a generalizable deepfake detection model by training convoluted neural networks (CNNs) to classify human facial features in videos. The study formulated the research questions: “How effectively does the developed model provide reliable generalizations?” A CNN model was trained to distinguish between real and fake videos using the facial features of human subjects in videos. The model was trained, validated, and tested using the FaceForensiq++ dataset, which contains more than 500,000 frames and subsets of the DFDC dataset, totaling more than 22,000 videos. The study demonstrated high generalizability, as the accuracy of the unknown dataset was only marginally (about 1%) lower than that of the known dataset. The findings of this study indicate that detection systems can be more generalizable, lighter, and faster by focusing on just a small region (the human face) of an entire video.

关键词： Artificial Intelligence Convoluted Neural Networks Deepfake GANs Generalization Deep Learning facial features Video Frames

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Visual Detection of Parkinson's Disease via facial features Recognition

Visual Detection of Parkinson's Disease via Facial Features ...

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2021中国智能自动化大会(CIAC2021)

作者： Xinyao Hou Shengmei Qin Jianbo Su Department of Automation Shanghai Jiao Tong University Zhongshan Hospital

Parkinson’s disease(PD) is a widely concerned neurodegenerative disease, due to its high prevalence in the elderly population. In this paper, a simple automated framework for PD detection is designed. The framework is proposed by extracting geometric and texture features based on facial visual information. Geometric features are defined via interrelationships of the facial landmarks, indicating the physical information of facial features. Texture features are extracted with a method fused with Local Binary Pattern(LBP) and Gray-level Co-occurrence Matrix(GLCM) that enhance the discriminative ability of the system, indicating the digital information of facial features. The proposed method performs well with a variety of classifiers, and the best result reaches 0.936 accuracy and 0.938 F score. Results indicate this simple automated framework for PD detection could provide a valuable tool for the clinical assessment of PD, which could assist in PD screening effectively.

关键词： Parkinson’s disease facial features Computer-aided diagnosis Machine learning

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Expression Complementary Disentanglement Network for facial Expression Recognition

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Chinese Journal of Electronics 2024年第3期33卷 742-752页

作者： Shanmin WANG Hui SHUAI Lei ZHU Qingshan LIU College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics College of Computer and Software Nanjing University of Information Science and Technology School of Information and Control Nanjing University of Information Science and Technology

Disentangling facial expressions from other disturbing facial attributes in face images is an essential topic for facial expression *** methods only care about facial expression disentanglement(FED)itself,ignoring the negative effects of other facial *** to the annotations on limited facial attributes,it is difficult for existing FED solutions to disentangle all disturbance from the input *** solve this issue,we propose an expression complementary disentanglement network(ECDNet).ECDNet proposes to finish the FED task during a face reconstruction process,so as to address all facial attributes during *** from traditional reconstruction models,ECDNet reconstructs face images by progressively generating and combining facial appearance and matching *** designs the expression incentive(EIE) and expression inhibition(EIN) mechanisms,inducing the model to characterize the disentangled expression and complementary parts *** geometry and appearance,generated in the reconstructed process,are dealt with to represent facial expressions and complementary parts,*** combination of distinctive reconstruction model,EIE,and EIN mechanisms ensures the completeness and exactness of the FED *** results on RAF-DB,AffectNet,and CAER-S datasets have proven the effectiveness and superiority of ECDNet.

关键词： Geometry Image recognition Annotations Face recognition Task analysis Image reconstruction facial features

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Identikit Creation with the Use of Genetic Algorithms

Identikit Creation with the Use of Genetic Algorithms

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2012 International Conference on Mechanical Materials and Manufacturing Engineering(ICMMME 2012)

作者： Milan Ková? Peter Schreiber Faculty of Material Science and Technology in Trnava Slovak University of Technology

The method for an identikit creating has been practically unchanged since its invention, despite the fact that it is low effective. By using genetic algorithms, faces are taken as wholes and are created by generations. Using crossover and mutation, they evolve themselves, so there is no need to work with individual parts. Witness chooses the best face in every generation, so he does not have to give a description. Faces are evolving until the witness is satisfied with the results.

关键词： Genetic algorithms facial features Selection tool Fitness Crossover

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