Mohamed W. Abo El-Soud^1,2,*, Tarek Gaber^2,3, 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 >

S. Karthiga^*, A. M. Abirami

Computer Systems Science and Engineering, Vol.42, No.3, pp. 851-866, 2022, DOI:10.32604/csse.2022.021935 - 08 February 2022

Abstract Much attention has been given to the Internet of Things (IoT) by citizens, industries, governments, and universities for applications like smart buildings, environmental monitoring, health care and so on. With IoT, network connectivity is facilitated between smart devices from anyplace and anytime. IoT-based health monitoring systems are gaining popularity and acceptance for continuous monitoring and detect health abnormalities from the data collected. Electrocardiographic (ECG) signals are widely used for heart diseases detection. A novel method has been proposed in this work for ECG monitoring using IoT techniques. In this work, a two-stage approach is employed.… More >

Dina M. Ibrahim^1,2,*, Nada M. Elshennawy²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 331-348, 2022, DOI:10.32604/cmes.2022.016419 - 24 January 2022

Abstract Dates are an important part of human nutrition. Dates are high in essential nutrients and provide a number of health benefits. Date fruits are also known to protect against a number of diseases, including cancer and heart disease. Date fruits have several sizes, colors, tastes, and values. There are a lot of challenges facing the date producers. One of the most significant challenges is the classification and sorting of dates. But there is no public dataset for date fruits, which is a major limitation in order to improve the performance of convolutional neural networks (CNN)… More >

Erssa Arif^1,*, Syed Khuram Shahzad², Rehman Mustafa¹, Muhammad Arfan Jaffar³, Muhammad Waseem Iqbal⁴

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 909-922, 2022, DOI:10.32604/iasc.2022.021061 - 17 November 2021

Abstract The conventional surveillance and control system of Closed-Circuit Television (CCTV) cameras require human resource supervision. Almost all the criminal activities take place using weapons mostly handheld gun, revolver, or pistol. Automatic gun detection is a vital requirement now-a-days. The use of real-time object detection system for the improvement of surveillance is a promising application of Convolutional Neural Networks (CNN). We are concerned about the real-time detection of weapons for the surveillance cameras, so we focused on the implementation and comparison of faster approaches such as Region (R-CNN) and Region Fully Convolutional Networks (R-FCN) with feature… More >

Mohammed A. Alghassab^*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 637-652, 2022, DOI:10.32604/cmc.2022.019527 - 07 September 2021

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… More >

D. Srinivasa Rao¹, Ramesh Babu Ch², V. Sravan Kiran¹, N. Rajasekhar^3,*, Kalyanapu Srinivas⁴, P. Shilhora Akshay¹, G. Sai Mohan¹, B. Lalith Bharadwaj¹

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 161-176, 2022, DOI:10.32604/iasc.2022.017706 - 03 September 2021

Abstract

Plant diseases have become a major threat in farming and provision of food. Various plant diseases have affected the natural growth of the plants and the infected plants are the leading factors for loss of crop production. The manual detection and identification of the plant diseases require a careful and observative examination through expertise. To overcome manual testing procedures an automated identification and detection can be implied which provides faster, scalable and precisive solutions. In this research, the contributions of our work are threefold. Firstly, a bi-linear convolution neural network (Bi-CNNs) for plant leaf disease

… More >

Reham Alabduljabbar^*, Hala Alshamlan

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 831-847, 2021, DOI:10.32604/cmc.2021.018402 - 04 June 2021

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… More >

Khalid A. AlShalfan¹, Mohammed Zakariah^2,*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 689-704, 2021, DOI:10.32604/cmc.2021.015989 - 22 March 2021

Abstract Currently, distracted driving is among the most important causes of traffic accidents. Consequently, intelligent vehicle driving systems have become increasingly important. Recently, interest in driver-assistance systems that detect driver actions and help them drive safely has increased. In these studies, although some distinct data types, such as the physical conditions of the driver, audio and visual features, and vehicle information, are used, the primary data source is images of the driver that include the face, arms, and hands taken with a camera inside the car. In this study, an architecture based on a convolution neural More >

Hamid A. Jalab¹, Ala’a R. Al-Shamasneh¹, Hadil Shaiba², Rabha W. Ibrahim^3,4,*, Dumitru Baleanu^5,6,7

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2061-2075, 2021, DOI:10.32604/cmc.2021.015170 - 05 February 2021

Abstract Recently, many rapid developments in digital medical imaging have made further contributions to health care systems. The segmentation of regions of interest in medical images plays a vital role in assisting doctors with their medical diagnoses. Many factors like image contrast and quality affect the result of image segmentation. Due to that, image contrast remains a challenging problem for image segmentation. This study presents a new image enhancement model based on fractional Rényi entropy for the segmentation of kidney MRI scans. The proposed work consists of two stages: enhancement by fractional Rényi entropy, and MRI… More >

Ruaa A. Al-Falluji^1,*, Zainab Dalaf Katheeth², Bashar Alathari²

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1301-1313, 2021, DOI:10.32604/cmc.2020.013232 - 26 November 2020

Abstract The latest studies with radiological imaging techniques indicate that X-ray images provide valuable details on the Coronavirus disease 2019 (COVID-19). The usage of sophisticated artificial intelligence technology (AI) and the radiological images can help in diagnosing the disease reliably and addressing the problem of the shortage of trained doctors in remote villages. In this research, the automated diagnosis of Coronavirus disease was performed using a dataset of X-ray images of patients with severe bacterial pneumonia, reported COVID-19 disease, and normal cases. The goal of the study is to analyze the achievements for medical image recognition… More >