Kyeongseok Jang¹, Seongsoo Cho², Kwang Chul Son^3,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3537-3551, 2023, DOI:10.32604/cmc.2023.030557

Abstract In the proposed paper, a parallel structure type Generative Adversarial Network (GAN) using edge and texture information is proposed. In the existing GAN-based model, many learning iterations had to be given to obtaining an output that was somewhat close to the original data, and noise and distortion occurred in the output image even when learning was performed. To solve this problem, the proposed model consists of two generators and three discriminators to propose a network in the form of a parallel structure. In the network, each edge information and texture information were received as inputs, learning was performed, and each… More >

Ushaa Eswaran^1,*, S. Anand²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1917-1928, 2023, DOI:10.32604/csse.2023.032523

Abstract Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance according to the combined models… More >

Yuanyuan Wang^1,*, Rui Wang², Xiaofeng Ren³, Junan Lei²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1951-1972, 2023, DOI:10.32604/cmes.2023.026112

Abstract The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function. To form dense mandatory constraints and improve matching accuracy, the traditional binocular reconstruction technology was improved threefold. First, a single moving laser line was introduced to carry out global scanning constraints on the target, which would well overcome the difficulty of installing and recognizing excessive laser lines. Second, four kinds of improved algorithms, namely, disparity replacement, superposition synthesis, subregion segmentation, and subregion segmentation centroid enhancement, were established based on different constraint mechanism. Last, the improved binocular reconstruction test device was developed to realize the dual… More >

C. Preethi^*, M. Mohamed Sathik, S. Shajun Nisha

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2971-2988, 2023, DOI:10.32604/csse.2023.033423

Abstract Three dimensional (3D) echocardiogram enables cardiologists to visualize suspicious cardiac structures in detail. In recent years, this three-dimensional echocardiogram carries important clinical value in virtual surgical simulation. However, this 3D echocardiogram involves a trade-off difficulty between accuracy and efficient computation in clinical diagnosis. This paper presents a novel Flip Directional 3D Volume Reconstruction (FD-3DVR) method for the reconstruction of echocardiogram images. The proposed method consists of two main steps: multiplanar volumetric imaging and 3D volume reconstruction. In the creation of multiplanar volumetric imaging, two-dimensional (2D) image pixels are mapped into voxels of the volumetric grid. As the obtained slices are… More >

Chaithra^1,*, G. M. Lingaraju², S. Jagannatha³

Computer Systems Science and Engineering, Vol.45, No.1, pp. 803-817, 2023, DOI:10.32604/csse.2023.028770

Abstract In the data retrieval process of the Data recommendation system, the matching prediction and similarity identification take place a major role in the ontology. In that, there are several methods to improve the retrieving process with improved accuracy and to reduce the searching time. Since, in the data recommendation system, this type of data searching becomes complex to search for the best matching for given query data and fails in the accuracy of the query recommendation process. To improve the performance of data validation, this paper proposed a novel model of data similarity estimation and clustering method to retrieve the… More >

Mutian Niu¹, Cheng-Hung Lo^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.24, No.1, pp. 1-3, 2022, DOI:10.32604/icces.2022.08669

Abstract Introduction:
Through a series of psychophysical experiments, this paper investigates the perceptual difference of roughness and texture on surface materials in immersive Virtual Reality (VR) viewing mode and traditional 2D viewing mode. Visual perception is generally considered as the most reliable perceptual mechanism, which is often studied for exploring and revealing the relationship between cognitive processes and visual information transmission [1]. VR provides users with a strong sense of presence. Furthermore, it utilizes our stereoscopic vision to form a vivid impression of depth. This stereoscopic depth effect thus became a key factor differentiating the experiences in VR and traditional 2D… More >

Saleem Mustafa¹, Arfan Jaffar¹, Muhammad Waseem Iqbal^2,*, Asma Abubakar², Abdullah S. Alshahrani³, Ahmed Alghamdi⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2205-2218, 2023, DOI:10.32604/iasc.2023.029549

Abstract Melanoma is of the lethal and rare types of skin cancer. It is curable at an initial stage and the patient can survive easily. It is very difficult to screen all skin lesion patients due to costly treatment. Clinicians are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders, pigment networks, and the color of melanoma. These challenges are required an automated system to classify the clinical features of melanoma and non-melanoma disease. The trained clinicians can overcome the issues such as low contrast, lesions varying in size, color, and the existence of… More >

Pierre-Frédéric Villard^1,*, Maureen Boudart², Ioana Ilea³, Fabien Pierre¹

FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.6, pp. 1639-1648, 2022, DOI:10.32604/fdmp.2022.021726

Abstract Industrial woven meshes are composed of metal materials and are often used in construction, industrial and residential activities or applications. The objective of this work is defect detection in industrial fabrics in the quality control stage. In order to overcome the limitations of manual methods, which are often tedious and time-consuming, we propose a strategy that can automatically detect defects in micrometric steel meshes by means of a Convolutional Neural Network. The database used for such a purpose comes from real problem data for anomaly detection in micrometric woven meshes. This detection is performed through supervised classification with a Convolutional… More >

Piao Yongfeng^*†‡§1, Jiang Chuner^*¶#1, Wang Lei^*†‡§, Yan Fengqin^*†‡§, Ye Zhimin^*†‡§, Fu Zhenfu^*†‡§, Jiang Haitao^*,**††, Jiang Yangming^‡‡, Wang Fangzheng^*†‡§

Oncology Research, Vol.28, No.6, pp. 605-613, 2020, DOI:10.3727/096504020X16022401878096

Abstract The aim of this study was to explore the predictive role of pretreatment MRI-based radiomics on early response of neoadjuvant chemotherapy (NAC) in locoregionally advanced nasopharyngeal carcinoma (NPC) patients. Between January 2016 and December 2016, a total of 108 newly diagnosed NPC patients who were hospitalized in the Cancer Hospital of the University of Chinese Academy of Sciences were reviewed. All patients had complete data of enhanced MR of nasopharynx before treatment, and then received two to three cycles of TP-based NAC. After 2 cycles of NAC, enhanced MR of nasopharynx was conducted again. Compared with the enhanced MR images… More >

Yue Zhang^1,3,4, Pengyu Liu^1,2,3,4,*, Xiaowei Jia⁵, Shanji Chen², Tianyu Liu^1,3,4, Chang Liu^1,3,4

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3545-3556, 2022, DOI:10.32604/cmc.2022.028226

Abstract Versatile video coding (H.266/VVC), which was newly released by the Joint Video Exploration Team (JVET), introduces quad-tree plus multi-type tree (QTMT) partition structure on the basis of quad-tree (QT) partition structure in High Efficiency Video Coding (H.265/HEVC). More complicated coding unit (CU) partitioning processes in H.266/VVC significantly improve video compression efficiency, but greatly increase the computational complexity compared. The ultra-high encoding complexity has obstructed its real-time applications. In order to solve this problem, a CU partition algorithm using convolutional neural network (CNN) is proposed in this paper to speed up the H.266/VVC CU partition process. Firstly, 64 × 64 CU… More >