Anika Tahsin Meem¹, Mohammad Monirujjaman Khan^1,*, Mehedi Masud², Sultan Aljahdali²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1223-1240, 2022, DOI:10.32604/csse.2022.021563 - 10 November 2021

Abstract The COVID-19 pandemic has caused trouble in people’s daily lives and ruined several economies around the world, killing millions of people thus far. It is essential to screen the affected patients in a timely and cost-effective manner in order to fight this disease. This paper presents the prediction of COVID-19 with Chest X-Ray images, and the implementation of an image processing system operated using deep learning and neural networks. In this paper, a Deep Learning, Machine Learning, and Convolutional Neural Network-based approach for predicting Covid-19 positive and normal patients using Chest X-Ray pictures is proposed.… More >

Jakkrit Onshaunjit, Jakkree Srinonchat^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 355-367, 2022, DOI:10.32604/cmc.2022.017698 - 03 November 2021

Abstract An ideal printed circuit board (PCB) defect inspection system can detect defects and classify PCB defect types. Existing defect inspection technologies can identify defects but fail to classify all PCB defect types. This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types. In the proposed algorithmic scheme, fuzzy c-means clustering is used for image segmentation via image subtraction prior to defect detection. Arithmetic and logic operations, the circle hough transform (CHT), morphological reconstruction (MR), and connected component labeling (CCL) are used in defect classification. The algorithmic scheme achieves More >

V. Thanikachalam^1,*, S. Shanthi², K. Kalirajan³, Sayed Abdel-Khalek^4,5, Mohamed Omri⁶, Lotfi M. Ladhar⁷

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5667-5681, 2022, DOI:10.32604/cmc.2022.020965 - 11 October 2021

Abstract The rapid development of biomedical imaging modalities led to its wide application in disease diagnosis. Tongue-based diagnostic procedures are proficient and non-invasive in nature to carry out secondary diagnostic processes ubiquitously. Traditionally, physicians examine the characteristics of tongue prior to decision-making. In this scenario, to get rid of qualitative aspects, tongue images can be quantitatively inspected for which a new disease diagnosis model is proposed. This model can reduce the physical harm made to the patients. Several tongue image analytical methodologies have been proposed earlier. However, there is a need exists to design an intelligent… More >

Aayesha¹, Muhammad Bilal Qureshi², Muhammad Afzaal³, Muhammad Shuaib Qureshi⁴, Jeonghwan Gwak^5,6,7,8,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5601-5630, 2022, DOI:10.32604/cmc.2022.020348 - 11 October 2021

Abstract Detection of epileptic seizures on the basis of Electroencephalogram (EEG) recordings is a challenging task due to the complex, non-stationary and non-linear nature of these biomedical signals. In the existing literature, a number of automatic epileptic seizure detection methods have been proposed that extract useful features from EEG segments and classify them using machine learning algorithms. Some characterizing features of epileptic and non-epileptic EEG signals overlap; therefore, it requires that analysis of signals must be performed from diverse perspectives. Few studies analyzed these signals in diverse domains to identify distinguishing characteristics of epileptic EEG signals.… More >

Seonjae Kim, Dongsan Jun^*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3267-3279, 2022, DOI:10.32604/cmc.2022.020651 - 27 September 2021

Abstract Medical image compression is one of the essential technologies to facilitate real-time medical data transmission in remote healthcare applications. In general, image compression can introduce undesired coding artifacts, such as blocking artifacts and ringing effects. In this paper, we proposed a Multi-Scale Feature Attention Network (MSFAN) with two essential parts, which are multi-scale feature extraction layers and feature attention layers to efficiently remove coding artifacts of compressed medical images. Multi-scale feature extraction layers have four Feature Extraction (FE) blocks. Each FE block consists of five convolution layers and one CA block for weighted skip connection. More >

K. N. Vijeyakumar¹, S. Maragatharaj^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2543-2561, 2022, DOI:10.32604/cmc.2022.019789 - 27 September 2021

Abstract Approximate computing has received significant attention in the design of portable CMOS hardware for error-tolerant applications. This work proposes an approximate adder that to optimize area delay and achieve energy efficiency using Parallel Carry (PC) generation logic. For ‘n’ bits in input, the proposed algorithm use approximate addition for least n/2 significant bits and exact addition for most n/2 significant bits. A simple OR logic with no carry propagation is used to implement the approximate part. In the exact part, addition is performed using 4-bit adder blocks that implement PC at block level to reduce node capacitance… More >

Hanan A. Hosni Mahmoud, Amal H. Alharbi, Norah S. Alghamdi^*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1273-1286, 2022, DOI:10.32604/iasc.2022.020662 - 22 September 2021

Abstract In this paper we propose a computerized breast cancer detection and breast masses classification system utilizing mammograms. The motivation of the proposed method is to detect breast cancer tumors in early stages with more accuracy and less negative false cases. Our proposed method utilizes clustering of different features by segmenting the breast mammogram and then extracts deep features using the presented Convolution Neural Network (CNN). The extracted features are then combined with subjective features such as shape, texture and density. The combined features are then utilized by the Extreme Learning Machine Clustering (ELMC) algorithm to… More >

S. A. Shaban^*, D. L. Elsheweikh

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 817-834, 2022, DOI:10.32604/iasc.2022.019500 - 22 September 2021

Abstract The present paper proposes a novel system that automatically classifies the eight different blood groups according to the ABO and Rh blood group systems. The proposed system is developed by applying MATLAB’s image processing techniques on the blood sample images. These images are acquired from the laboratory using the slide test. It utilizes a mean filter for removing noise from blood sample images. In addition, the Contrast Limited Adaptive Histogram Equalization (CLAHE) is used for enhancing the image characteristics analysis. The proposed system also utilizes the automated threshold strategy (Otsu’s approach) for obtaining the blood… More >

Hanan A. Hosni Mahmoud^*, Doaa S. Khafga, Amal H. Alharbi

Computer Systems Science and Engineering, Vol.40, No.2, pp. 805-821, 2022, DOI:10.32604/csse.2022.019633 - 09 September 2021

Abstract Limbal Stem Cell Deficiency (LSCD) is an eye disease that can cause corneal opacity and vascularization. In its advanced stage it can lead to a degree of visual impairment. It involves the changing in the semispherical shape of the cornea to a drooping shape to downwards direction. LSCD is hard to be diagnosed at early stages. The color and texture of the cornea surface can provide significant information about the cornea affected by LSCD. Parameters such as shape and texture are very crucial to differentiate normal from LSCD cornea. Although several medical approaches exist, most… More >

Liying Zhu^*, Ang Wang, Fang Jin

FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.6, pp. 1213-1222, 2021, DOI:10.32604/fdmp.2021.017572 - 08 September 2021

Abstract In the present study, the laws of smoke diffusion during forest fires are determined using the general principles of fluid mechanics and dedicated data obtained experimentally using an “ad hoc” imaging technology. Experimental images mimicking smoke in a real scenario are used to extract some “statistics”. These in turn are used to obtain the “divergence” of the flow (this fluid-dynamic parameter describing the amount of air that converges to a certain place from the surroundings or vice versa). The results show that the divergence of the smoke depends on the outside airflow and finally tends to More >