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  • Open Access

    ARTICLE

    An Enhanced Deep Learning Method for Skin Cancer Detection and Classification

    Mohamed W. Abo El-Soud1,2,*, Tarek Gaber2,3, Mohamed Tahoun2, Abdullah Alourani1

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1109-1123, 2022, DOI:10.32604/cmc.2022.028561 - 18 May 2022

    Abstract The prevalence of melanoma skin cancer has increased in recent decades. The greatest risk from melanoma is its ability to broadly spread throughout the body by means of lymphatic vessels and veins. Thus, the early diagnosis of melanoma is a key factor in improving the prognosis of the disease. Deep learning makes it possible to design and develop intelligent systems that can be used in detecting and classifying skin lesions from visible-light images. Such systems can provide early and accurate diagnoses of melanoma and other types of skin diseases. This paper proposes a new method… More >

  • Open Access

    ARTICLE

    An Evolutionary Normalization Algorithm for Signed Floating-Point Multiply-Accumulate Operation

    Rajkumar Sarma1, Cherry Bhargava2, Ketan Kotecha3,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 481-495, 2022, DOI:10.32604/cmc.2022.024516 - 24 February 2022

    Abstract In the era of digital signal processing, like graphics and computation systems, multiplication-accumulation is one of the prime operations. A MAC unit is a vital component of a digital system, like different Fast Fourier Transform (FFT) algorithms, convolution, image processing algorithms, etcetera. In the domain of digital signal processing, the use of normalization architecture is very vast. The main objective of using normalization is to perform comparison and shift operations. In this research paper, an evolutionary approach for designing an optimized normalization algorithm is proposed using basic logical blocks such as Multiplexer, Adder etc. The… More >

  • Open Access

    ARTICLE

    COVID-19 Detection via a 6-Layer Deep Convolutional Neural Network

    Shouming Hou, Ji Han*

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 855-869, 2022, DOI:10.32604/cmes.2022.016621 - 13 December 2021

    Abstract Many people around the world have lost their lives due to COVID-19. The symptoms of most COVID-19 patients are fever, tiredness and dry cough, and the disease can easily spread to those around them. If the infected people can be detected early, this will help local authorities control the speed of the virus, and the infected can also be treated in time. We proposed a six-layer convolutional neural network combined with max pooling, batch normalization and Adam algorithm to improve the detection effect of COVID-19 patients. In the 10-fold cross-validation methods, our method is superior More >

  • Open Access

    ARTICLE

    Improved Dragonfly Optimizer for Intrusion Detection Using Deep Clustering CNN-PSO Classifier

    K. S. Bhuvaneshwari1, K. Venkatachalam2, S. Hubálovský3,*, P. Trojovský4, P. Prabu5

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5949-5965, 2022, DOI:10.32604/cmc.2022.020769 - 11 October 2021

    Abstract With the rapid growth of internet based services and the data generated on these services are attracted by the attackers to intrude the networking services and information. Based on the characteristics of these intruders, many researchers attempted to aim to detect the intrusion with the help of automating process. Since, the large volume of data is generated and transferred through network, the security and performance are remained an issue. IDS (Intrusion Detection System) was developed to detect and prevent the intruders and secure the network systems. The performance and loss are still an issue because… More >

  • Open Access

    ARTICLE

    Research on the Key Techniques of TCP Protocol Normalization for Mimic Defense Architecture

    Mingxing Zhu, Yansong Wang, Ruyun Zhang, Tianning Zhang, Heyuan Li, Hanguang Luo, Shunbin Li*

    Journal on Internet of Things, Vol.3, No.3, pp. 99-107, 2021, DOI:10.32604/jiot.2021.014921 - 16 December 2021

    Abstract The Mimic Defense (MD) is an endogenous security technology with the core technique of Dynamic Heterogeneous Redundancy (DHR) architecture. It can effectively resist unknown vulnerabilities, backdoors, and other security threats by schedule strategy, negative feedback control, and other mechanisms. To solve the problem that Cyber Mimic Defense devices difficulty of supporting the TCP protocol. This paper proposes a TCP protocol normalization scheme for DHR architecture. Theoretical analysis and experimental results show that this scheme can realize the support of DHR-based network devices to TCP protocol without affecting the security of mimicry defense architecture. More >

  • Open Access

    ARTICLE

    Generating Cartoon Images from Face Photos with Cycle-Consistent Adversarial Networks

    Tao Zhang1,2, Zhanjie Zhang1,2,*, Wenjing Jia3, Xiangjian He3, Jie Yang4

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2733-2747, 2021, DOI:10.32604/cmc.2021.019305 - 21 July 2021

    Abstract The generative adversarial network (GAN) is first proposed in 2014, and this kind of network model is machine learning systems that can learn to measure a given distribution of data, one of the most important applications is style transfer. Style transfer is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image. CYCLE-GAN is a classic GAN model, which has a wide range of scenarios in style transfer. Considering its unsupervised learning characteristics, the mapping is easy to be learned between an… More >

  • Open Access

    ARTICLE

    An Ensemble of Optimal Deep Learning Features for Brain Tumor Classification

    Ahsan Aziz1, Muhammad Attique1, Usman Tariq2, Yunyoung Nam3,*, Muhammad Nazir1, Chang-Won Jeong4, Reham R. Mostafa5, Rasha H. Sakr6

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2653-2670, 2021, DOI:10.32604/cmc.2021.018606 - 21 July 2021

    Abstract Owing to technological developments, Medical image analysis has received considerable attention in the rapid detection and classification of diseases. The brain is an essential organ in humans. Brain tumors cause loss of memory, vision, and name. In 2020, approximately 18,020 deaths occurred due to brain tumors. These cases can be minimized if a brain tumor is diagnosed at a very early stage. Computer vision researchers have introduced several techniques for brain tumor detection and classification. However, owing to many factors, this is still a challenging task. These challenges relate to the tumor size, the shape… More >

  • Open Access

    ARTICLE

    Estimating Age in Short Utterances Based on Multi-Class Classification Approach

    Ameer A. Badr1,2,*, Alia K. Abdul-Hassan2

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1713-1729, 2021, DOI:10.32604/cmc.2021.016732 - 13 April 2021

    Abstract Age estimation in short speech utterances finds many applications in daily life like human-robot interaction, custom call routing, targeted marketing, user-profiling, etc. Despite the comprehensive studies carried out to extract descriptive features, the estimation errors (i.e. years) are still high. In this study, an automatic system is proposed to estimate age in short speech utterances without depending on the text as well as the speaker. Firstly, four groups of features are extracted from each utterance frame using hybrid techniques and methods. After that, 10 statistical functionals are measured for each extracted feature dimension. Then, the… More >

  • Open Access

    ARTICLE

    Ensembling Neural Networks for User’s Indoor Localization Using Magnetic Field Data from Smartphones

    Imran Ashraf, Soojung Hur, Yousaf Bin Zikria, Yongwan Park*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2597-2620, 2021, DOI:10.32604/cmc.2021.016214 - 13 April 2021

    Abstract Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors: Smartphone heterogeneity and smaller data lengths. The use of multifarious smartphones cripples the performance of such approaches owing to the variability of the magnetic field data. In the same vein, smaller lengths of magnetic field data decrease the localization accuracy substantially. The current study proposes the use of multiple neural networks like deep neural network (DNN), long short term memory network (LSTM), and gated recurrent unit network (GRN) to perform indoor localization based on the embedded magnetic sensor of… More >

  • Open Access

    ARTICLE

    Performance of Lung Cancer Prediction Methods Using Different Classification Algorithms

    Yasemin Gültepe*

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2015-2028, 2021, DOI:10.32604/cmc.2021.014631 - 05 February 2021

    Abstract In 2018, 1.76 million people worldwide died of lung cancer. Most of these deaths are due to late diagnosis, and early-stage diagnosis significantly increases the likelihood of a successful treatment for lung cancer. Machine learning is a branch of artificial intelligence that allows computers to quickly identify patterns within complex and large datasets by learning from existing data. Machine-learning techniques have been improving rapidly and are increasingly used by medical professionals for the successful classification and diagnosis of early-stage disease. They are widely used in cancer diagnosis. In particular, machine learning has been used in… More >

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