Sukhendra Singh¹, Sur Singh Rawat, Manoj Gupta³, B. K. Tripathi⁴, Faisal Alanazi⁵, Arnab Majumdar⁶, Pattaraporn Khuwuthyakorn⁷, Orawit Thinnukool^7,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3063-3083, 2023, DOI:10.32604/cmc.2023.032363

Abstract Currently, breast cancer has been a major cause of deaths in women worldwide and the World Health Organization (WHO) has confirmed this. The severity of this disease can be minimized to the large extend, if it is diagnosed properly at an early stage of the disease. Therefore, the proper treatment of a patient having cancer can be processed in better way, if it can be diagnosed properly as early as possible using the better algorithms. Moreover, it has been currently observed that the deep neural networks have delivered remarkable performance for detecting cancer in histopathological images of breast tissues. To… More >

Sunisa Tavaen, Sayan Kaennakham^*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4081-4098, 2023, DOI:10.32604/cmc.2023.032329

Abstract This work focuses on radial basis functions containing no parameters with the main objective being to comparatively explore more of their effectiveness. For this, a total of sixteen forms of shapeless radial basis functions are gathered and investigated under the context of the pattern recognition problem through the structure of radial basis function neural networks, with the use of the Representational Capability (RC) algorithm. Different sizes of datasets are disturbed with noise before being imported into the algorithm as ‘training/testing’ datasets. Each shapeless radial basis function is monitored carefully with effectiveness criteria including accuracy, condition number (of the interpolation matrix),… More >

Safi Ullah^1,2, Seong-Ho Song^1,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2999-3014, 2023, DOI:10.32604/cmc.2023.032326

Abstract Due to highly underdetermined nature of Single Image Super-Resolution (SISR) problem, deep learning neural networks are required to be more deeper to solve the problem effectively. One of deep neural networks successful in the Super-Resolution (SR) problem is ResNet which can render the capability of deeper networks with the help of skip connections. However, zero padding (ZP) scheme in the network restricts benefits of skip connections in SRResNet and its performance as the ratio of the number of pure input data to that of zero padded data increases. In this paper. we consider the ResNet with Partial Convolution based Padding… More >

Zaid Nidhal Khudhair^1,4, Farhan Mohamed², Amjad Rehman^3,*, Tanzila Saba³, Saeed Ali bahaj³

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4135-4147, 2023, DOI:10.32604/cmc.2023.032315

Abstract This paper presents an improved approach for detecting copy-move forgery based on singular value decomposition (SVD). It is a block-based method where the image is scanned from left to right and top to down by a sliding window with a determined size. At each step, the SVD is determined. First, the diagonal matrix’s maximum value (norm) is selected (representing the scaling factor for SVD and a fixed value for each set of matrix elements even when rotating the matrix or scaled). Then, the similar norms are grouped, and each leading group is separated into many subgroups (elements of each subgroup… More >

Sajadul Hassan Kumhar¹, Syed Immamul Ansarullah², Akber Abid Gardezi³, Shafiq Ahmad⁴, Abdelaty Edrees Sayed⁴, Muhammad Shafiq^5,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3899-3912, 2023, DOI:10.32604/cmc.2023.032290

Abstract English to Urdu machine translation is still in its beginning and lacks simple translation methods to provide motivating and adequate English to Urdu translation. In order to make knowledge available to the masses, there should be mechanisms and tools in place to make things understandable by translating from source language to target language in an automated fashion. Machine translation has achieved this goal with encouraging results. When decoding the source text into the target language, the translator checks all the characteristics of the text. To achieve machine translation, rule-based, computational, hybrid and neural machine translation approaches have been proposed to… More >

Mahmoud Ragab^1,2,3,*, Mohammed W. Al-Rabia^4,5, Sami Saeed Binyamin⁶, Ahmed A. Aldarmahi^7,8

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2889-2903, 2023, DOI:10.32604/cmc.2023.032192

Abstract With the increasing and rapid growth rate of COVID-19 cases, the healthcare scheme of several developed countries have reached the point of collapse. An important and critical steps in fighting against COVID-19 is powerful screening of diseased patients, in such a way that positive patient can be treated and isolated. A chest radiology image-based diagnosis scheme might have several benefits over traditional approach. The accomplishment of artificial intelligence (AI) based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition systems. This study develops an… More >

Muhammad Aasim Qureshi¹, Muhammad Asif², Saira Anwar³, Umar Shaukat¹, Atta-ur-Rahman⁴, Muhammad Adnan Khan^5,*, Amir Mosavi^6,7,8

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2589-2605, 2023, DOI:10.32604/cmc.2023.032173

Abstract With the advancements in internet facilities, people are more inclined towards the use of online services. The service providers shelve their items for e-users. These users post their feedbacks, reviews, ratings, etc. after the use of the item. The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items. Sentiment Analysis (SA) is a technique that performs such decision analysis. This research targets the ranking and rating through sentiment analysis of these reviews, on different aspects. As a case study, Songs are opted to design and test the decision… More >

Seongung Jo¹, Heung-Seon Oh^1,*, Sanghun Im¹, Gibaeg Kim¹, Seonho Kim²

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2967-2980, 2023, DOI:10.32604/cmc.2023.031983

Abstract Analyzing Research and Development (R&D) trends is important because it can influence future decisions regarding R&D direction. In typical trend analysis, topic or technology taxonomies are employed to compute the popularities of the topics or codes over time. Although it is simple and effective, the taxonomies are difficult to manage because new technologies are introduced rapidly. Therefore, recent studies exploit deep learning to extract pre-defined targets such as problems and solutions. Based on the recent advances in question answering (QA) using deep learning, we adopt a multi-turn QA model to extract problems and solutions from Korean R&D reports. With the… More >

Jawad Rasheed^1,*, Shtwai Alsubai²

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4239-4259, 2023, DOI:10.32604/cmc.2023.031969

Abstract Humankind is facing another deadliest pandemic of all times in history, caused by COVID-19. Apart from this challenging pandemic, World Health Organization (WHO) considers tuberculosis (TB) as a preeminent infectious disease due to its high infection rate. Generally, both TB and COVID-19 severely affect the lungs, thus hardening the job of medical practitioners who can often misidentify these diseases in the current situation. Therefore, the time of need calls for an immediate and meticulous automatic diagnostic tool that can accurately discriminate both diseases. As one of the preliminary smart health systems that examine three clinical states (COVID-19, TB, and normal… More >

Nishant Behar^*, Manish Shrivastava

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3371-3389, 2023, DOI:10.32604/cmc.2023.031949

Abstract Breast cancer is the most prevalent cancer among women, and diagnosing it early is vital for successful treatment. The examination of images captured during biopsies plays an important role in determining whether a patient has cancer or not. However, the stochastic patterns, varying intensities of colors, and the large sizes of these images make it challenging to identify and mark malignant regions in them. Against this backdrop, this study proposes an approach to the pixel categorization based on the genetic algorithm (GA) and principal component analysis (PCA). The spatial features of the images were extracted using various filters, and the… More >