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  • Open Access


    Improved Shark Smell Optimization Algorithm for Human Action Recognition

    Inzamam Mashood Nasir1,*, Mudassar Raza1, Jamal Hussain Shah1, Muhammad Attique Khan2, Yun-Cheol Nam3, Yunyoung Nam4,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2667-2684, 2023, DOI:10.32604/cmc.2023.035214

    Abstract Human Action Recognition (HAR) in uncontrolled environments targets to recognition of different actions from a video. An effective HAR model can be employed for an application like human-computer interaction, health care, person tracking, and video surveillance. Machine Learning (ML) approaches, specifically, Convolutional Neural Network (CNN) models had been widely used and achieved impressive results through feature fusion. The accuracy and effectiveness of these models continue to be the biggest challenge in this field. In this article, a novel feature optimization algorithm, called improved Shark Smell Optimization (iSSO) is proposed to reduce the redundancy of extracted features. This proposed technique is… More >

  • Open Access


    Deep Learning-Based Sign Language Recognition for Hearing and Speaking Impaired People

    Mrim M. Alnfiai*

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1653-1669, 2023, DOI:10.32604/iasc.2023.033577

    Abstract Sign language is mainly utilized in communication with people who have hearing disabilities. Sign language is used to communicate with people having developmental impairments who have some or no interaction skills. The interaction via Sign language becomes a fruitful means of communication for hearing and speech impaired persons. A Hand gesture recognition system finds helpful for deaf and dumb people by making use of human computer interface (HCI) and convolutional neural networks (CNN) for identifying the static indications of Indian Sign Language (ISL). This study introduces a shark smell optimization with deep learning based automated sign language recognition (SSODL-ASLR) model… More >

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