Fan Yang¹, Jie Xu^1,*, Haoliang Wei¹, Meng Ye², Mingzhu Xu¹, Qiuru Fu¹, Lingfei Ren³, Zhengwen Huang⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2963-2980, 2022, DOI:10.32604/cmc.2022.022810 - 07 December 2021

Abstract Zanthoxylum bungeanum Maxim, generally called prickly ash, is widely grown in China. Zanthoxylum rust is the main disease affecting the growth and quality of Zanthoxylum. Traditional method for recognizing the degree of infection of Zanthoxylum rust mainly rely on manual experience. Due to the complex colors and shapes of rust areas, the accuracy of manual recognition is low and difficult to be quantified. In recent years, the application of artificial intelligence technology in the agricultural field has gradually increased. In this paper, based on the DeepLabV2 model, we proposed a Zanthoxylum rust image segmentation model… More >

Vatsala Anand¹, Sheifali Gupta¹, Deepika Koundal^2,*, Shubham Mahajan³, Amit Kant Pandit³, Atef Zaguia⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3145-3160, 2022, DOI:10.32604/cmc.2022.022788 - 07 December 2021

Abstract Biomedical image analysis has been exploited considerably by recent technology involvements, carrying about a pattern shift towards ‘automation’ and ‘error free diagnosis’ classification methods with markedly improved accurate diagnosis productivity and cost effectiveness. This paper proposes an automated deep learning model to diagnose skin disease at an early stage by using Dermoscopy images. The proposed model has four convolutional layers, two maxpool layers, one fully connected layer and three dense layers. All the convolutional layers are using the kernel size of 3 * 3 whereas the maxpool layer is using the kernel size of 2… More >

CSS Anupama¹, T. J. Benedict Jose², Heba F. Eid³, Nojood O Aljehane⁴, Fahd N. Al-Wesabi^5,*, Marwa Obayya⁶, Anwer Mustafa Hilal⁷

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3969-3983, 2022, DOI:10.32604/cmc.2022.022701 - 07 December 2021

Abstract Biomedical images are used for capturing the images for diagnosis process and to examine the present condition of organs or tissues. Biomedical image processing concepts are identical to biomedical signal processing, which includes the investigation, improvement, and exhibition of images gathered using x-ray, ultrasound, MRI, etc. At the same time, cervical cancer becomes a major reason for increased women's mortality rate. But cervical cancer is an identified at an earlier stage using regular pap smear images. In this aspect, this paper devises a new biomedical pap smear image classification using cascaded deep forest (BPSIC-CDF) model… More >

Mesfer Al Duhayyim¹, Amani Abdulrahman Albraikan², Fahd N. Al-Wesabi^3,4, Hiba M. Burbur⁵, Mohammad Alamgeer⁶, Anwer Mustafa Hilal⁷, Manar Ahmed Hamza^7,*, Mohammed Rizwanullah⁷

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3953-3968, 2022, DOI:10.32604/cmc.2022.022692 - 07 December 2021

Abstract Short-term traffic flow prediction (TFP) is an important area in intelligent transportation system (ITS), which is used to reduce traffic congestion. But the avail of traffic flow data with temporal features and periodic features are susceptible to weather conditions, making TFP a challenging issue. TFP process are significantly influenced by several factors like accident and weather. Particularly, the inclement weather conditions may have an extreme impact on travel time and traffic flow. Since most of the existing TFP techniques do not consider the impact of weather conditions on the TF, it is needed to develop… More >

Noha E. El-Attar^1,*, Sahar F. Sabbeh^1,2, Heba Fasihuddin², Wael A. Awad³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2249-2269, 2022, DOI:10.32604/cmc.2022.022673 - 07 December 2021

Abstract The outbreak of Covid-19 has taken the lives of many patients so far. The symptoms of COVID-19 include muscle pains, loss of taste and smell, coughs, fever, and sore throat, which can lead to severe cases of breathing difficulties, organ failure, and death. Thus, the early detection of the virus is very crucial. COVID-19 can be detected using clinical tests, making us need to know the most important symptoms/features that can enhance the decision process. In this work, we propose a modified multilayer perceptron (MLP) with feature selection (MLPFS) to predict the positive COVID-19 cases… More >

Abdulqader M. Almars^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3091-3106, 2022, DOI:10.32604/cmc.2022.022609 - 07 December 2021

Abstract Depression is a common mental health issue that affects a large percentage of people all around the world. Usually, people who suffer from this mood disorder have issues such as low concentration, dementia, mood swings, and even suicide. A social media platform like Twitter allows people to communicate as well as share photos and videos that reflect their moods. Therefore, the analysis of social media content provides insight into individual moods, including depression. Several studies have been conducted on depression detection in English and less in Arabic. The detection of depression from Arabic social media… More >

Usra Yasmeen¹, Muhammad Attique Khan¹, Usman Tariq², Junaid Ali Khan¹, Muhammad Asfand E. Yar³, Ch. Avais Hanif⁴, Senghour Mey⁵, Yunyoung Nam^6,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3667-3684, 2022, DOI:10.32604/cmc.2022.022264 - 07 December 2021

Abstract Agriculture is the backbone of each country, and almost 50% of the population is directly involved in farming. In Pakistan, several kinds of fruits are produced and exported the other countries. Citrus is an important fruit, and its production in Pakistan is higher than the other fruits. However, the diseases of citrus fruits such as canker, citrus scab, blight, and a few more impact the quality and quantity of this Fruit. The manual diagnosis of these diseases required an expert person who is always a time-consuming and costly procedure. In the agriculture sector, deep learning… More >

Ahmed Elaraby^1,*, Walid Hamdy², Madallah Alruwaili³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 4019-4031, 2022, DOI:10.32604/cmc.2022.022161 - 07 December 2021

Abstract Plant diseases are a major impendence to food security, and due to a lack of key infrastructure in many regions of the world, quick identification is still challenging. Harvest losses owing to illnesses are a severe problem for both large farming structures and rural communities, motivating our mission. Because of the large range of diseases, identifying and classifying diseases with human eyes is not only time-consuming and labor intensive, but also prone to being mistaken with a high error rate. Deep learning-enabled breakthroughs in computer vision have cleared the road for smartphone-assisted plant disease and… More >

Ahmed R. Abas¹, Ibrahim Elhenawy¹, Mahinda Zidan^2,*, Mahmoud Othman²

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2943-2961, 2022, DOI:10.32604/cmc.2022.021671 - 07 December 2021

Abstract Due to the widespread usage of social media in our recent daily lifestyles, sentiment analysis becomes an important field in pattern recognition and Natural Language Processing (NLP). In this field, users’ feedback data on a specific issue are evaluated and analyzed. Detecting emotions within the text is therefore considered one of the important challenges of the current NLP research. Emotions have been widely studied in psychology and behavioral science as they are an integral part of the human nature. Emotions describe a state of mind of distinct behaviors, feelings, thoughts and experiences. The main objective… More >

Muhammad Zulqarnain¹, Rozaida Ghazali^1,*, Habib Shah², Lokman Hakim Ismail¹, Abdullah Alsheddy³, Maqsood Mahmud⁴

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3051-3068, 2022, DOI:10.32604/cmc.2022.021629 - 07 December 2021

Abstract Air pollution is a significant problem in modern societies since it has a serious impact on human health and the environment. Particulate Matter (PM_2.5) is a type of air pollution that contains of interrupted elements with a diameter less than or equal to 2.5 m. For risk assessment and epidemiological investigations, a better knowledge of the spatiotemporal variation of PM_2.5 concentration in a constant space-time area is essential. Conventional spatiotemporal interpolation approaches commonly relying on robust presumption by limiting interpolation algorithms to those with explicit and basic mathematical expression, ignoring a plethora of hidden but crucial… More >