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  • 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 >

  • Open Access

    ARTICLE

    Single-Choice Aided Marking System Research Based on Back Propagation Neural Network

    Yunzuo Zhang*, Yi Li, Wei Guo, Lei Huo, Jiayu Zhang, Kaina Guo

    Journal of Cyber Security, Vol.3, No.1, pp. 45-54, 2021, DOI:10.32604/jcs.2021.017071 - 30 April 2021

    Abstract In the field of educational examination, automatic marking technology plays an essential role in improving the efficiency of marking and liberating the labor force. At present, the implementation of the policy of expanding erolments has caused a serious decline in the teacher-student ratio in colleges and universities. The traditional marking system based on Optical Mark Reader technology can no longer meet the requirements of liberating the labor force of teachers in small and medium-sized examinations. With the development of image processing and artificial neural network technology, the recognition of handwritten character in the field of… More >

  • Open Access

    ARTICLE

    Adaptive Median Filtering Algorithm Based on Divide and Conquer and Its Application in CAPTCHA Recognition

    Wentao Ma1, Jiaohua Qin1,*, Xuyu Xiang1, Yun Tan1, Yuanjing Luo1, Neal N. Xiong2

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 665-677, 2019, DOI:10.32604/cmc.2019.05683

    Abstract As the first barrier to protect cyberspace, the CAPTCHA has made significant contributions to maintaining Internet security and preventing malicious attacks. By researching the CAPTCHA, we can find its vulnerability and improve the security of CAPTCHA. Recently, many studies have shown that improving the image preprocessing effect of the CAPTCHA, which can achieve a better recognition rate by the state-of-the-art machine learning algorithms. There are many kinds of noise and distortion in the CAPTCHA images of this experiment. We propose an adaptive median filtering algorithm based on divide and conquer in this paper. Firstly, the More >

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