Kai Chen^*, Jinwei Wang, Jiawei Zhang

Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 15-24, 2022, DOI:10.32604/jihpp.2022.029006 - 17 June 2022

Abstract In recent years, machine learning has become more and more popular, especially the continuous development of deep learning technology, which has brought great revolutions to many fields. In tasks such as image classification, natural language processing, information hiding, multimedia synthesis, and so on, the performance of deep learning has far exceeded the traditional algorithms. However, researchers found that although deep learning can train an accurate model through a large amount of data to complete various tasks, the model is vulnerable to the example which is modified artificially. This technology is called adversarial attacks, while the More >

Nagwan Abdel Samee¹, El-Sayed M. El-Kenawy^2,3, Ghada Atteia^1,*, Mona M. Jamjoom⁴, Abdelhameed Ibrahim⁵, Abdelaziz A. Abdelhamid^6,7, Noha E. El-Attar⁸, Tarek Gaber^9,10, Adam Slowik¹¹, Mahmoud Y. Shams¹²

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4193-4210, 2022, DOI:10.32604/cmc.2022.031147 - 16 June 2022

Abstract As corona virus disease (COVID-19) is still an ongoing global outbreak, countries around the world continue to take precautions and measures to control the spread of the pandemic. Because of the excessive number of infected patients and the resulting deficiency of testing kits in hospitals, a rapid, reliable, and automatic detection of COVID-19 is in extreme need to curb the number of infections. By analyzing the COVID-19 chest X-ray images, a novel metaheuristic approach is proposed based on hybrid dipper throated and particle swarm optimizers. The lung region was segmented from the original chest X-ray… More >

Vasumathi Devi Majety¹, N. Sharmili², Chinmaya Ranjan Pattanaik³, E. Laxmi Lydia⁴, Subhi R. M. Zeebaree⁵, Sarmad Nozad Mahmood⁶, Ali S. Abosinnee⁷, Ahmed Alkhayyat^8,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4393-4406, 2022, DOI:10.32604/cmc.2022.031109 - 16 June 2022

Abstract Histopathology is the investigation of tissues to identify the symptom of abnormality. The histopathological procedure comprises gathering samples of cells/tissues, setting them on the microscopic slides, and staining them. The investigation of the histopathological image is a problematic and laborious process that necessitates the expert’s knowledge. At the same time, deep learning (DL) techniques are able to derive features, extract data, and learn advanced abstract data representation. With this view, this paper presents an ensemble of handcrafted with deep learning enabled histopathological image classification (EHCDL-HIC) model. The proposed EHCDL-HIC technique initially performs Weiner filtering based… More >

Areej A. Malibari¹, Marwa Obayya², Mohamed K. Nour³, Amal S. Mehanna⁴, Manar Ahmed Hamza^5,*, Abu Sarwar Zamani⁵, Ishfaq Yaseen⁵, Abdelwahed Motwakel⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4123-4138, 2022, DOI:10.32604/cmc.2022.030492 - 16 June 2022

Abstract With the rapid increase of new cases with an increased mortality rate, cancer is considered the second and most deadly disease globally. Breast cancer is the most widely affected cancer worldwide, with an increased death rate percentage. Due to radiologists’ processing of mammogram images, many computer-aided diagnoses have been developed to detect breast cancer. Early detection of breast cancer will reduce the death rate worldwide. The early diagnosis of breast cancer using the developed computer-aided diagnosis (CAD) systems still needed to be enhanced by incorporating innovative deep learning technologies to improve the accuracy and sensitivity… More >

Muhammad Shahid Amin¹, Jamal Hussain Shah¹, Mussarat Yasmin¹, Ghulam Jillani Ansari², Muhamamd Attique Khan³, Usman Tariq⁴, Ye Jin Kim⁵, Byoungchol Chang^6,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4423-4439, 2022, DOI:10.32604/cmc.2022.030432 - 16 June 2022

Abstract Due to rapid development in Artificial Intelligence (AI) and Deep Learning (DL), it is difficult to maintain the security and robustness of these techniques and algorithms due to emergence of novel term adversary sampling. Such technique is sensitive to these models. Thus, fake samples cause AI and DL model to produce diverse results. Adversarial attacks that successfully implemented in real world scenarios highlight their applicability even further. In this regard, minor modifications of input images cause “Adversarial Attacks” that altered the performance of competing attacks dramatically. Recently, such attacks and defensive strategies are gaining lot… More >

Olfat M. Mirza¹, G. Jose Moses², R. Rajender³, E. Laxmi Lydia⁴, Seifedine Kadry⁵, Cheadchai Me-Ead⁶, Orawit Thinnukool^7,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3757-3769, 2022, DOI:10.32604/cmc.2022.030428 - 16 June 2022

Abstract Presently, customer retention is essential for reducing customer churn in telecommunication industry. Customer churn prediction (CCP) is important to predict the possibility of customer retention in the quality of services. Since risks of customer churn also get essential, the rise of machine learning (ML) models can be employed to investigate the characteristics of customer behavior. Besides, deep learning (DL) models help in prediction of the customer behavior based characteristic data. Since the DL models necessitate hyperparameter modelling and effort, the process is difficult for research communities and business people. In this view, this study designs More >

Abeer Abdulaziz AlArfaj, Hanan Ahmed Hosni Mahmoud^*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4231-4244, 2022, DOI:10.32604/cmc.2022.030090 - 16 June 2022

Abstract In recent research, deep learning algorithms have presented effective representation learning models for natural languages. The deep learning-based models create better data representation than classical models. They are capable of automated extraction of distributed representation of texts. In this research, we introduce a new tree Extractive text summarization that is characterized by fitting the text structure representation in knowledge base training module, and also addresses memory issues that were not addresses before. The proposed model employs a tree structured mechanism to generate the phrase and text embedding. The proposed architecture mimics the tree configuration of… More >

Amal Al-Rasheed¹, Jaber S. Alzahrani², Majdy M. Eltahir³, Abdullah Mohamed⁴, Anwer Mustafa Hilal^5,*, Abdelwahed Motwakel⁵, Abu Sarwar Zamani⁵, Mohamed I. Eldesouki⁶

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3275-3290, 2022, DOI:10.32604/cmc.2022.029823 - 16 June 2022

Abstract The biomedical data classification process has received significant attention in recent times due to a massive increase in the generation of healthcare data from various sources. The developments of artificial intelligence (AI) and machine learning (ML) models assist in the effectual design of medical data classification models. Therefore, this article concentrates on the development of optimal Stacked Long Short Term Memory Sequence-to-Sequence Autoencoder (OSAE-LSTM) model for biomedical data classification. The presented OSAE-LSTM model intends to classify the biomedical data for the existence of diseases. Primarily, the OSAE-LSTM model involves min-max normalization based pre-processing to scale More >

Haikuo Peng¹, Yun Tan^1,*, Hao Tang², Ling Tan², Xuyu Xiang¹, Yongjun Wang², Neal N. Xiong³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2757-2771, 2022, DOI:10.32604/cmc.2022.029727 - 16 June 2022

Abstract Aortic dissection (AD) is one of the most serious diseases with high mortality, and its diagnosis mainly depends on computed tomography (CT) results. Most existing automatic diagnosis methods of AD are only suitable for AD recognition, which usually require preselection of CT images and cannot be further classified to different types. In this work, we constructed a dataset of 105 cases with a total of 49021 slices, including 31043 slices expert-level annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep learning. The proposed region of interest (RoI) extraction algorithm based More >

Trong Hieu Luu¹, Phan Nguyen Ky Phuc^2,*, Zhiqiu Yu³, Duy Dung Pham¹, Huu Trong Cao¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3251-3262, 2022, DOI:10.32604/cmc.2022.029663 - 16 June 2022

Abstract In recent years, the COVID-19 pandemic has negatively impacted all aspects of social life. Due to ease in the infected method, i.e., through small liquid particles from the mouth or the nose when people cough, sneeze, speak, sing, or breathe, the virus can quickly spread and create severe problems for people’s health. According to some research as well as World Health Organization (WHO) recommendation, one of the most economical and effective methods to prevent the spread of the pandemic is to ask people to wear the face mask in the public space. A face mask… More >