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  • Open Access

    ARTICLE

    Arithmetic Optimization with Ensemble Deep Transfer Learning Based Melanoma Classification

    K. Kalyani1, Sara A Althubiti2, Mohammed Altaf Ahmed3, E. Laxmi Lydia4, Seifedine Kadry5, Neunggyu Han6, Yunyoung Nam6,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 149-164, 2023, DOI:10.32604/cmc.2023.033005

    Abstract Melanoma is a skin disease with high mortality rate while early diagnoses of the disease can increase the survival chances of patients. It is challenging to automatically diagnose melanoma from dermoscopic skin samples. Computer-Aided Diagnostic (CAD) tool saves time and effort in diagnosing melanoma compared to existing medical approaches. In this background, there is a need exists to design an automated classification model for melanoma that can utilize deep and rich feature datasets of an image for disease classification. The current study develops an Intelligent Arithmetic Optimization with Ensemble Deep Transfer Learning Based Melanoma Classification (IAOEDTT-MC) model. The proposed IAOEDTT-MC… More >

  • Open Access

    ARTICLE

    Metaheuristic Optimization of Time Series Models for Predicting Networks Traffic

    Reem Alkanhel1, El-Sayed M. El-kenawy2,3, D. L. Elsheweikh4, Abdelaziz A. Abdelhamid5,6, Abdelhameed Ibrahim7, Doaa Sami Khafaga8,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 427-442, 2023, DOI:10.32604/cmc.2023.032885

    Abstract Traffic prediction of wireless networks attracted many researchers and practitioners during the past decades. However, wireless traffic frequently exhibits strong nonlinearities and complicated patterns, which makes it challenging to be predicted accurately. Many of the existing approaches for predicting wireless network traffic are unable to produce accurate predictions because they lack the ability to describe the dynamic spatial-temporal correlations of wireless network traffic data. In this paper, we proposed a novel meta-heuristic optimization approach based on fitness grey wolf and dipper throated optimization algorithms for boosting the prediction accuracy of traffic volume. The proposed algorithm is employed to optimize the… More >

  • Open Access

    ARTICLE

    Zero-Index Metamaterial Superstrates UWB Antenna for Microwave Imaging Detection

    Mohd Aminudin Jamlos1,*, Nur Amirah Othman1, Wan Azani Mustafa2, Mohd Faizal Jamlos3, Mohamad Nur Khairul Hafizi Rohani2

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 277-292, 2023, DOI:10.32604/cmc.2023.032840

    Abstract Metamaterials (MTM) can enhance the properties of microwaves and also exceed some limitations of devices used in technical practice. Note that the antenna is the element for realizing a microwave imaging (MWI) system since it is where signal transmission and absorption occur. Ultra-Wideband (UWB) antenna superstrates with MTM elements to ensure the signal transmitted from the antenna reaches the tumor and is absorbed by the same antenna. The lack of conventional head imaging techniques, for instance, Magnetic Resonance Imaging (MRI) and Computerized Tomography (CT)-scan, has been demonstrated in the paper focusing on the point of failure of these techniques for… More >

  • Open Access

    ARTICLE

    License Plate Recognition via Attention Mechanism

    Longjuan Wang1,2, Chunjie Cao1,2, Binghui Zou1,2, Jun Ye1,2,*, Jin Zhang3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1801-1814, 2023, DOI:10.32604/cmc.2023.032785

    Abstract License plate recognition technology use widely in intelligent traffic management and control. Researchers have been committed to improving the speed and accuracy of license plate recognition for nearly 30 years. This paper is the first to propose combining the attention mechanism with YOLO-v5 and LPRnet to construct a new license plate recognition model (LPR-CBAM-Net). Through the attention mechanism CBAM (Convolutional Block Attention Module), the importance of different feature channels in license plate recognition can be re-calibrated to obtain proper attention to features. Force information to achieve the purpose of improving recognition speed and accuracy. Experimental results show that the model… More >

  • Open Access

    ARTICLE

    Automated Artificial Intelligence Empowered White Blood Cells Classification Model

    Mohammad Yamin1, Abdullah M. Basahel1, Mona Abusurrah2, Sulafah M Basahel3, Sachi Nandan Mohanty4, E. Laxmi Lydia5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 409-425, 2023, DOI:10.32604/cmc.2023.032432

    Abstract White blood cells (WBC) or leukocytes are a vital component of the blood which forms the immune system, which is accountable to fight foreign elements. The WBC images can be exposed to different data analysis approaches which categorize different kinds of WBC. Conventionally, laboratory tests are carried out to determine the kind of WBC which is erroneous and time consuming. Recently, deep learning (DL) models can be employed for automated investigation of WBC images in short duration. Therefore, this paper introduces an Aquila Optimizer with Transfer Learning based Automated White Blood Cells Classification (AOTL-WBCC) technique. The presented AOTL-WBCC model executes… More >

  • Open Access

    ARTICLE

    Blood Vessel Segmentation with Classification Model for Diabetic Retinopathy Screening

    Abdullah O. Alamoudi1,*, Sarah Mohammed Allabun2

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2265-2281, 2023, DOI:10.32604/cmc.2023.032429

    Abstract Biomedical image processing is finding useful in healthcare sector for the investigation, enhancement, and display of images gathered by distinct imaging technologies. Diabetic retinopathy (DR) is an illness caused by diabetes complications and leads to irreversible injury to the retina blood vessels. Retinal vessel segmentation techniques are a basic element of automated retinal disease screening system. In this view, this study presents a novel blood vessel segmentation with deep learning based classification (BVS-DLC) model for DR diagnosis using retinal fundus images. The proposed BVS-DLC model involves different stages of operations such as preprocessing, segmentation, feature extraction, and classification. Primarily, the… More >

  • Open Access

    ARTICLE

    Weighted De-Synchronization Based Resource Allocation in Wireless Networks

    Kimchheang Chhea1, Dara Ron1, Jung-Ryun Lee1,2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1815-1826, 2023, DOI:10.32604/cmc.2023.032376

    Abstract Considering the exponential growth of wireless devices with data-starving applications fused with artificial intelligence, the significance of wireless network scalability using distributed behavior and fairness among users is a crucial feature in guaranteeing reliable service to numerous users in the network environment. The Kuramoto model is described as nonlinear self-sustained phase oscillators spinning at varying intrinsic frequencies connected through the sine of their phase differences and displays a phase transition at a specific coupling strength, in which a mutual behavior is accomplished. In this work, we apply the Kuramoto model to achieve a weighted fair resource allocation in a wireless… More >

  • Open Access

    ARTICLE

    Gastrointestinal Diseases Classification Using Deep Transfer Learning and Features Optimization

    Mousa Alhajlah1, Muhammad Nouman Noor2, Muhammad Nazir2, Awais Mahmood1,*, Imran Ashraf3, Tehmina Karamat4

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2227-2245, 2023, DOI:10.32604/cmc.2023.031890

    Abstract Gastrointestinal diseases like ulcers, polyps’, and bleeding are increasing rapidly in the world over the last decade. On average 0.7 million cases are reported worldwide every year. The main cause of gastrointestinal diseases is a Helicobacter Pylori (H. Pylori) bacterium that presents in more than 50% of people around the globe. Many researchers have proposed different methods for gastrointestinal disease using computer vision techniques. Few of them focused on the detection process and the rest of them performed classification. The major challenges that they faced are the similarity of infected and healthy regions that misleads the correct classification accuracy. In… More >

  • Open Access

    ARTICLE

    Lung Cancer Segmentation with Three-Parameter Logistic Type Distribution Model

    Debnath Bhattacharyya1, Eali. Stephen Neal Joshua2, N. Thirupathi Rao2, Yung-cheol Byun3,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1447-1465, 2023, DOI:10.32604/cmc.2023.031878

    Abstract Lung cancer is the leading cause of mortality in the world affecting both men and women equally. When a radiologist just focuses on the patient’s body, it increases the amount of strain on the radiologist and the likelihood of missing pathological information such as abnormalities are increased. One of the primary objectives of this research work is to develop computer-assisted diagnosis and detection of lung cancer. It also intends to make it easier for radiologists to identify and diagnose lung cancer accurately. The proposed strategy which was based on a unique image feature, took into consideration the spatial interaction of… More >

  • Open Access

    ARTICLE

    Symbiotic Organisms Search with Deep Learning Driven Biomedical Osteosarcoma Detection and Classification

    Abdullah M. Basahel1, Mohammad Yamin1, Sulafah M. Basahel2, Mona M. Abusurrah3, K.Vijaya Kumar4, E. Laxmi Lydia5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 133-148, 2023, DOI:10.32604/cmc.2023.031786

    Abstract Osteosarcoma is one of the rare bone cancers that affect the individuals aged between 10 and 30 and it incurs high death rate. Early diagnosis of osteosarcoma is essential to improve the survivability rate and treatment protocols. Traditional physical examination procedure is not only a time-consuming process, but it also primarily relies upon the expert’s knowledge. In this background, the recently developed Deep Learning (DL) models can be applied to perform decision making. At the same time, hyperparameter optimization of DL models also plays an important role in influencing overall classification performance. The current study introduces a novel Symbiotic Organisms… More >

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