S. S. Saranya^*, N. Sabiyath Fatima

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1857-1874, 2022, DOI:10.32604/cmc.2022.019621

Abstract The Internet of Things (IoT) role is instrumental in the technological advancement of the healthcare industry. Both the hardware and the core level of software platforms are the progress resulted from the accompaniment of Medicine 4.0. Healthcare IoT systems are the emergence of this foresight. The communication systems between the sensing nodes and the processors; and the processing algorithms to produce output obtained from the data collected by the sensors are the major empowering technologies. At present, many new technologies supplement these empowering technologies. So, in this research work, a practical feature extraction and classification technique is suggested for handling… More >

Mohammed A. Alghassab^*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 637-652, 2022, DOI:10.32604/cmc.2022.019527

Abstract Printed Circuit Boards (PCBs) are very important for proper functioning of any electronic device. PCBs are installed in almost all the electronic device and their functionality is dependent on the perfection of PCBs. If PCBs do not function properly then the whole electric machine might fail. So, keeping this in mind researchers are working in this field to develop error free PCBs. Initially these PCBs were examined by the human beings manually, but the human error did not give good results as sometime defected PCBs were categorized as non-defective. So, researchers and experts transformed this manual traditional examination to automated… More >

M. Buvana¹, K. Muthumayil², S. Senthil kumar³, Jamel Nebhen⁴, Sultan S. Alshamrani⁵, Ihsan Ali^6,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 43-58, 2022, DOI:10.32604/cmc.2022.019331

Abstract Coronavirus (COVID-19) outbreak was first identified in Wuhan, China in December 2019. It was tagged as a pandemic soon by the WHO being a serious public medical condition worldwide. In spite of the fact that the virus can be diagnosed by qRT-PCR, COVID-19 patients who are affected with pneumonia and other severe complications can only be diagnosed with the help of Chest X-Ray (CXR) and Computed Tomography (CT) images. In this paper, the researchers propose to detect the presence of COVID-19 through images using Best deep learning model with various features. Impressive features like Speeded-Up Robust Features (SURF), Features from… More >

Anas Basalamah¹, Shadikur Rahman^2,*

Computer Systems Science and Engineering, Vol.40, No.1, pp. 375-388, 2022, DOI:10.32604/csse.2022.016949

Abstract This paper demonstrates empirical research on using convolutional neural networks (CNN) of deep learning techniques to classify X-rays of COVID-19 patients versus normal patients by feature extraction. Feature extraction is one of the most significant phases for classifying medical X-rays radiography that requires inclusive domain knowledge. In this study, CNN architectures such as VGG-16, VGG-19, RestNet50, RestNet18 are compared, and an optimized model for feature extraction in X-ray images from various domains involving several classes is proposed. An X-ray radiography classifier with TensorFlow GPU is created executing CNN architectures and our proposed optimized model for classifying COVID-19 (Negative or Positive).… More >

Yu Xue^1,2,*, Chen Chen¹, ChiShe Wang², Linguo Li³, Romany F. Mansour⁴

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 973-982, 2021, DOI:10.32604/iasc.2021.017607

Abstract Face recognition technology has many usages in the real-world applications, and it has generated extensive interest in recent years. However, the amount of data in a digital image is growing explosively, taking up a lot of storage and transmission resources. There is a lot of redundancy in an image data representation. Thus, image compression has become a hot topic. The principal component analysis (PCA) can effectively remove the correlation of an image and condense the image information into a characteristic image with several main components. At the same time, it can restore different data images according to their principal components… More >

Revathi Jothiramalingam¹, Anitha Jude², Duraisamy Jude Hemanth^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 875-906, 2021, DOI: 10.32604/cmes.2021.016485

Abstract The 12-lead ECG aids in the diagnosis of myocardial infarction and is helpful in the prediction of cardiovascular disease complications. It does, though, have certain drawbacks. For other electrocardiographic anomalies such as Left Bundle Branch Block and Left Ventricular Hypertrophy syndrome, the ECG signal with Myocardial Infarction is difficult to interpret. These diseases cause variations in the ST portion of the ECG signal. It reduces the clarity of ECG signals, making it more difficult to diagnose these diseases. As a result, the specialist is misled into making an erroneous diagnosis by using the incorrect therapeutic technique. Based on these concepts,… More >

K. Muthumayil¹, S. Manikandan², S. Srinivasan³, José Escorcia-Gutierrez^4,*, Margarita Gamarra⁵, Romany F. Mansour⁶

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2031-2044, 2021, DOI:10.32604/cmc.2021.017116

Abstract White Blood Cell (WBC) cancer or leukemia is one of the serious cancers that threaten the existence of human beings. In spite of its prevalence and serious consequences, it is mostly diagnosed through manual practices. The risks of inappropriate, sub-standard and wrong or biased diagnosis are high in manual methods. So, there is a need exists for automatic diagnosis and classification method that can replace the manual process. Leukemia is mainly classified into acute and chronic types. The current research work proposed a computer-based application to classify the disease. In the feature extraction stage, we use excellent physical properties to… More >

Yanling An¹, Shaohai Hu^1,*, Shuaiqi Liu^2,3, Jie Zhao^2,3,*, Yu-Dong Zhang⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 203-222, 2021, DOI:10.32604/cmes.2021.015159

Abstract This paper proposes a computer-aided diagnosis system which can automatically detect thyroid nodules (TNs) and discriminate them as benign or malignant. The system firstly uses variational level set active contour with gradients and phase information to complete automatic extraction of the boundaries of thyroid nodules images. Then according to thyroid ultrasound images and clinical diagnostic criteria, a new feature extraction method based on the fusion of shape, gray and texture is explored. Due to the imbalance of thyroid sample classes, this paper introduces a weight factor to improve support vector machine, offering different classes of samples with different weights. Finally,… More >

Reham Alabduljabbar^*, Hala Alshamlan

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 831-847, 2021, DOI:10.32604/cmc.2021.018402

Abstract The worldwide mortality rate due to cancer is second only to cardiovascular diseases. The discovery of image processing, latest artificial intelligence techniques, and upcoming algorithms can be used to effectively diagnose and prognose cancer faster and reduce the mortality rate. Efficiently applying these latest techniques has increased the survival chances during recent years. The research community is making significant continuous progress in developing automated tools to assist dermatologists in decision making. The datasets used for the experimentation and analysis are ISBI 2016, ISBI 2017, and HAM 10000. In this work pertained models are used to extract the efficient feature. The… More >

Jehyeok Rew, Hyungjoon Kim, Eenjun Hwang^*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 801-817, 2021, DOI:10.32604/cmc.2021.017892

Abstract Objective and quantitative assessment of skin conditions is essential for cosmeceutical studies and research on skin aging and skin regeneration. Various handcraft-based image processing methods have been proposed to evaluate skin conditions objectively, but they have unavoidable disadvantages when used to analyze skin features accurately. This study proposes a hybrid segmentation scheme consisting of Deeplab v3+ with an Inception-ResNet-v2 backbone, LightGBM, and morphological processing (MP) to overcome the shortcomings of handcraft-based approaches. First, we apply Deeplab v3+ with an Inception-ResNet-v2 backbone for pixel segmentation of skin wrinkles and cells. Then, LightGBM and MP are used to enhance the pixel segmentation… More >