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  • Open Access

    ARTICLE

    Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

    Nizheen A. Ali1, Ramadhan J. Mstafa2,3,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1451-1469, 2023, DOI:10.32604/csse.2023.039957

    Abstract With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of video steganography, which is a technique that hides data within a video cover to avoid detection. The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency. This paper proposes a new method to video steganography, which involves utilizing a Genetic Algorithm (GA) for identifying the Region of Interest (ROI) in the cover video. The ROI… More >

  • Open Access

    ARTICLE

    A Method of Multimodal Emotion Recognition in Video Learning Based on Knowledge Enhancement

    Hanmin Ye1,2, Yinghui Zhou1, Xiaomei Tao3,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1709-1732, 2023, DOI:10.32604/csse.2023.039186

    Abstract With the popularity of online learning and due to the significant influence of emotion on the learning effect, more and more researches focus on emotion recognition in online learning. Most of the current research uses the comments of the learning platform or the learner’s expression for emotion recognition. The research data on other modalities are scarce. Most of the studies also ignore the impact of instructional videos on learners and the guidance of knowledge on data. Because of the need for other modal research data, we construct a synchronous multimodal data set for analyzing learners’ emotional states in online learning… More >

  • Open Access

    REVIEW

    Video-Based Interventions for Adolescents and Young Adults with Autism Spectrum Disorder: A Systematic Review

    Mohammed Al Jaffal*

    International Journal of Mental Health Promotion, Vol.25, No.8, pp. 881-890, 2023, DOI:10.32604/ijmhp.2023.028982

    Abstract Many individuals with autism spectrum disorder (ASD) experience delays in the development of social and communications skills, which can limit their opportunities in higher education and employment resulting in an overall negative impact to their quality of life. This systematic review identifies 15 studies that explored the effectiveness of Video-Based Interventions (VBIs) for those with ASD during the critical years of adolescence and young adulthood. The 15 studies described herein found this to be an effective intervention for this population for the improvement of their vocational, daily living, and academic skills. In addition, VBIs allow for the maintenance and generalization… More >

  • Open Access

    ARTICLE

    Abnormal Behavior Detection Using Deep-Learning-Based Video Data Structuring

    Min-Jeong Kim1, Byeong-Uk Jeon1, Hyun Yoo2, Kyungyong Chung3,*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2371-2386, 2023, DOI:10.32604/iasc.2023.040310

    Abstract With the increasing number of digital devices generating a vast amount of video data, the recognition of abnormal image patterns has become more important. Accordingly, it is necessary to develop a method that achieves this task using object and behavior information within video data. Existing methods for detecting abnormal behaviors only focus on simple motions, therefore they cannot determine the overall behavior occurring throughout a video. In this study, an abnormal behavior detection method that uses deep learning (DL)-based video-data structuring is proposed. Objects and motions are first extracted from continuous images by combining existing DL-based image analysis models. The… More >

  • Open Access

    ARTICLE

    Visual Motion Segmentation in Crowd Videos Based on Spatial-Angular Stacked Sparse Autoencoders

    Adel Hafeezallah1, Ahlam Al-Dhamari2,3,*, Syed Abd Rahman Abu-Bakar2

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 593-611, 2023, DOI:10.32604/csse.2023.039479

    Abstract Visual motion segmentation (VMS) is an important and key part of many intelligent crowd systems. It can be used to figure out the flow behavior through a crowd and to spot unusual life-threatening incidents like crowd stampedes and crashes, which pose a serious risk to public safety and have resulted in numerous fatalities over the past few decades. Trajectory clustering has become one of the most popular methods in VMS. However, complex data, such as a large number of samples and parameters, makes it difficult for trajectory clustering to work well with accurate motion segmentation results. This study introduces a… More >

  • Open Access

    ARTICLE

    « Sans tabou »
    Une web-série pour aborder la sexualité chez les jeunes patients atteints de cancer

    F. Ait-Kaci, S. Vanderosieren, C. Lervat

    Psycho-Oncologie, Vol.16, No.3, pp. 289-293, 2022, DOI:10.3166/pson-2022-0205

    Abstract Même bouleversée par le cancer, la sexualité peut rester une source de satisfaction pour les jeunes patients. Or, dans l’esprit général, sexualité et cancer figurent comme deux tabous, deux figures antinomiques qui ne peuvent coexister ensemble. Pour dépasser ce paradoxe, la websérie Sans tabou se propose comme un outil de médiation spécifique à la tranche d’âge 17–25 ans abordant avec acuité et humour le thème de la vie amoureuse et sexuelle lors d’un cancer. Ses objectifs sont d’encourager les professionnels de santé à approcher ce sujet de manière ludique et didactique, de combattre les idées reçues sur le cancer, les… More >

  • Open Access

    ARTICLE

    Fuzzy Rule-Based Model to Train Videos in Video Surveillance System

    A. Manju1, A. Revathi2, M. Arivukarasi1, S. Hariharan3, V. Umarani4, Shih-Yu Chen5,*, Jin Wang6

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 905-920, 2023, DOI:10.32604/iasc.2023.038444

    Abstract With the proliferation of the internet, big data continues to grow exponentially, and video has become the largest source. Video big data introduces many technological challenges, including compression, storage, transmission, analysis, and recognition. The increase in the number of multimedia resources has brought an urgent need to develop intelligent methods to organize and process them. The integration between Semantic link Networks and multimedia resources provides a new prospect for organizing them with their semantics. The tags and surrounding texts of multimedia resources are used to measure their semantic association. Two evaluation methods including clustering and retrieval are performed to measure… More >

  • Open Access

    ARTICLE

    Automated Video-Based Face Detection Using Harris Hawks Optimization with Deep Learning

    Latifah Almuqren1, Manar Ahmed Hamza2,*, Abdullah Mohamed3, Amgad Atta Abdelmageed2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4917-4933, 2023, DOI:10.32604/cmc.2023.037738

    Abstract Face recognition technology automatically identifies an individual from image or video sources. The detection process can be done by attaining facial characteristics from the image of a subject face. Recent developments in deep learning (DL) and computer vision (CV) techniques enable the design of automated face recognition and tracking methods. This study presents a novel Harris Hawks Optimization with deep learning-empowered automated face detection and tracking (HHODL-AFDT) method. The proposed HHODL-AFDT model involves a Faster region based convolution neural network (RCNN)-based face detection model and HHO-based hyperparameter optimization process. The presented optimal Faster RCNN model precisely recognizes the face and… More >

  • Open Access

    ARTICLE

    A Sentence Retrieval Generation Network Guided Video Captioning

    Ou Ye1,2, Mimi Wang1, Zhenhua Yu1,*, Yan Fu1, Shun Yi1, Jun Deng2

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5675-5696, 2023, DOI:10.32604/cmc.2023.037503

    Abstract Currently, the video captioning models based on an encoder-decoder mainly rely on a single video input source. The contents of video captioning are limited since few studies employed external corpus information to guide the generation of video captioning, which is not conducive to the accurate description and understanding of video content. To address this issue, a novel video captioning method guided by a sentence retrieval generation network (ED-SRG) is proposed in this paper. First, a ResNeXt network model, an efficient convolutional network for online video understanding (ECO) model, and a long short-term memory (LSTM) network model are integrated to construct… More >

  • Open Access

    ARTICLE

    ISHD: Intelligent Standing Human Detection of Video Surveillance for the Smart Examination Environment

    Wu Song1, Yayuan Tang2,3,*, Wenxue Tan1, Sheng Ren1

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 509-526, 2023, DOI:10.32604/cmes.2023.026933

    Abstract In the environment of smart examination rooms, it is important to quickly and accurately detect abnormal behavior (human standing) for the construction of a smart campus. Based on deep learning, we propose an intelligent standing human detection (ISHD) method based on an improved single shot multibox detector to detect the target of standing human posture in the scene frame of exam room video surveillance at a specific examination stage. ISHD combines the MobileNet network in a single shot multibox detector network, improves the posture feature extractor of a standing person, merges prior knowledge, and introduces transfer learning in the training… More >

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