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  • Open Access


    Hajj Crowd Management Using CNN-Based Approach

    Waleed Albattah1,*, Muhammad Haris Kaka Khel2, Shabana Habib1, Muhammad Islam3, Sheroz Khan3,4, Kushsairy Abdul Kadir2

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2183-2197, 2021, DOI:10.32604/cmc.2020.014227

    Abstract Hajj as the Muslim holy pilgrimage, attracts millions of humans to Mecca every year. According to statists, the pilgrimage has attracted close to 2.5 million pilgrims in 2019, and at its peak, it has attracted over 3 million pilgrims in 2012. It is considered as the world’s largest human gathering. Safety makes one of the main concerns with regards to managing the large crowds and ensuring that stampedes and other similar overcrowding accidents are avoided. This paper presents a crowd management system using image classification and an alarm system for managing the millions of crowds during Hajj. The image classification… More >

  • Open Access


    An Efficient Image Analysis Framework for the Classification of Glioma Brain Images Using CNN Approach

    Ravi Samikannu1, *, Rohini Ravi2, Sivaram Murugan3, Bakary Diarra4

    CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1133-1142, 2020, DOI:10.32604/cmc.2020.08578

    Abstract The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours. The detection of tumors is performed with the help of automatic computing technique as presented in the proposed work. The non-active cells in brain region are known to be benign and they will never cause the death of the patient. These non-active cells follow a uniform pattern in brain and have lower density than the surrounding pixels. The Magnetic Resonance (MR) image contrast is improved by the cost map construction technique. The deep learning algorithm for differentiating the normal brain… More >

  • Open Access


    CNN Approaches for Classification of Indian Leaf Species Using Smartphones

    M. Vilasini1, *, P. Ramamoorthy2

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1445-1472, 2020, DOI:10.32604/cmc.2020.08857

    Abstract Leaf species identification leads to multitude of societal applications. There is enormous research in the lines of plant identification using pattern recognition. With the help of robust algorithms for leaf identification, rural medicine has the potential to reappear as like the previous decades. This paper discusses CNN based approaches for Indian leaf species identification from white background using smartphones. Variations of CNN models over the features like traditional shape, texture, color and venation apart from the other miniature features of uniformity of edge patterns, leaf tip, margin and other statistical features are explored for efficient leaf classification. More >

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