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  • Open Access

    ARTICLE

    CNN Based Features Extraction and Selection Using EPO Optimizer for Cotton Leaf Diseases Classification

    Mehwish Zafar1, Javeria Amin2, Muhammad Sharif1, Muhammad Almas Anjum3, Seifedine Kadry4,5,6, Jungeun Kim7,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2779-2793, 2023, DOI:10.32604/cmc.2023.035860 - 08 October 2023

    Abstract Worldwide cotton is the most profitable cash crop. Each year the production of this crop suffers because of several diseases. At an early stage, computerized methods are used for disease detection that may reduce the loss in the production of cotton. Although several methods are proposed for the detection of cotton diseases, however, still there are limitations because of low-quality images, size, shape, variations in orientation, and complex background. Due to these factors, there is a need for novel methods for features extraction/selection for the accurate cotton disease classification. Therefore in this research, an optimized… More >

  • Open Access

    ARTICLE

    An Efficient and Robust Hand Gesture Recognition System of Sign Language Employing Finetuned Inception-V3 and Efficientnet-B0 Network

    Adnan Hussain1, Sareer Ul Amin2, Muhammad Fayaz3, Sanghyun Seo4,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3509-3525, 2023, DOI:10.32604/csse.2023.037258 - 03 April 2023

    Abstract Hand Gesture Recognition (HGR) is a promising research area with an extensive range of applications, such as surgery, video game techniques, and sign language translation, where sign language is a complicated structured form of hand gestures. The fundamental building blocks of structured expressions in sign language are the arrangement of the fingers, the orientation of the hand, and the hand’s position concerning the body. The importance of HGR has increased due to the increasing number of touchless applications and the rapid growth of the hearing-impaired population. Therefore, real-time HGR is one of the most effective… More >

  • Open Access

    ARTICLE

    CE-EEN-B0: Contour Extraction Based Extended EfficientNet-B0 for Brain Tumor Classification Using MRI Images

    Abishek Mahesh1, Deeptimaan Banerjee1, Ahona Saha1, Manas Ranjan Prusty2,*, A. Balasundaram2

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5967-5982, 2023, DOI:10.32604/cmc.2023.033920 - 28 December 2022

    Abstract A brain tumor is the uncharacteristic progression of tissues in the brain. These are very deadly, and if it is not diagnosed at an early stage, it might shorten the affected patient’s life span. Hence, their classification and detection play a critical role in treatment. Traditional Brain tumor detection is done by biopsy which is quite challenging. It is usually not preferred at an early stage of the disease. The detection involves Magnetic Resonance Imaging (MRI), which is essential for evaluating the tumor. This paper aims to identify and detect brain tumors based on their… More >

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