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  • Open Access


    Robust Interactive Method for Hand Gestures Recognition Using Machine Learning

    Amal Abdullah Mohammed Alteaimi1,*, Mohamed Tahar Ben Othman1,2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 577-595, 2022, DOI:10.32604/cmc.2022.023591

    Abstract The Hand Gestures Recognition (HGR) System can be employed to facilitate communication between humans and computers instead of using special input and output devices. These devices may complicate communication with computers especially for people with disabilities. Hand gestures can be defined as a natural human-to-human communication method, which also can be used in human-computer interaction. Many researchers developed various techniques and methods that aimed to understand and recognize specific hand gestures by employing one or two machine learning algorithms with a reasonable accuracy. This work aims to develop a powerful hand gesture recognition model with a 100% recognition rate. We… More >

  • Open Access


    Video Surveillance-Based Urban Flood Monitoring System Using a Convolutional Neural Network

    R. Dhaya1,*, R. Kanthavel2

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 183-192, 2022, DOI:10.32604/iasc.2022.021538

    Abstract The high prevalence of urban flooding in the world is increasing rapidly with the rise in extreme weather events. Consequently, this research uses an Automatic Flood Monitoring System (ARMS) through a video surveillance camera. Initially, videos are collected from a surveillance camera and converted into video frames. After converting the video frames, the water level can be identified by using a Histogram of oriented Gradient (HoG), which is used to remove the functionality. Completing the extracted features, the frames are enhanced by using a median filter to remove the unwanted noise from the image. The next step is water level… More >

  • Open Access


    Traffic Flow Statistics Method Based on Deep Learning and Multi-Feature Fusion

    Liang Mu, Hong Zhao*, Yan Li, Xiaotong Liu, Junzheng Qiu, Chuanlong Sun

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 465-483, 2021, DOI:10.32604/cmes.2021.017276

    Abstract Traffic flow statistics have become a particularly important part of intelligent transportation. To solve the problems of low real-time robustness and accuracy in traffic flow statistics. In the DeepSort tracking algorithm, the Kalman filter (KF), which is only suitable for linear problems, is replaced by the extended Kalman filter (EKF), which can effectively solve nonlinear problems and integrate the Histogram of Oriented Gradient (HOG) of the target. The multi-target tracking framework was constructed with YOLO V5 target detection algorithm. An efficient and long-running Traffic Flow Statistical framework (TFSF) is established based on the tracking framework. Virtual lines are set up… More >

  • Open Access


    Pashto Characters Recognition Using Multi-Class Enabled Support Vector Machine

    Sulaiman Khan1, Shah Nazir1, Habib Ullah Khan2,*, Anwar Hussain1

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2831-2844, 2021, DOI:10.32604/cmc.2021.015054

    Abstract During the last two decades significant work has been reported in the field of cursive language’s recognition especially, in the Arabic, the Urdu and the Persian languages. The unavailability of such work in the Pashto language is because of: the absence of a standard database and of significant research work that ultimately acts as a big barrier for the research community. The slight change in the Pashto characters’ shape is an additional challenge for researchers. This paper presents an efficient OCR system for the handwritten Pashto characters based on multi-class enabled support vector machine using manifold feature extraction techniques. These… More >

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