Jian Kang¹, Wanshu Fan¹, Yijing Li², Rui Liu¹, Dongsheng Zhou^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 607-629, 2023, DOI:10.32604/cmes.2023.024420

Abstract With the advancement of image sensing technology, estimating 3D human pose from monocular video has become a hot research topic in computer vision. 3D human pose estimation is an essential prerequisite for subsequent action analysis and understanding. It empowers a wide spectrum of potential applications in various areas, such as intelligent transportation, human-computer interaction, and medical rehabilitation. Currently, some methods for 3D human pose estimation in monocular video employ temporal convolutional network (TCN) to extract inter-frame feature relationships, but the majority of them suffer from insufficient inter-frame feature relationship extractions. In this paper, we decompose the 3D joint location regression… More >

Amarendra Reddy Panyala^1,2, M. Baskar^3,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3883-3899, 2023, DOI:10.32604/csse.2023.037050

Abstract The deep learning models are identified as having a significant impact on various problems. The same can be adapted to the problem of brain tumor classification. However, several deep learning models are presented earlier, but they need better classification accuracy. An efficient Multi-Feature Approximation Based Convolution Neural Network (CNN) model (MFA-CNN) is proposed to handle this issue. The method reads the input 3D Magnetic Resonance Imaging (MRI) images and applies Gabor filters at multiple levels. The noise-removed image has been equalized for its quality by using histogram equalization. Further, the features like white mass, grey mass, texture, and shape are… More >

Qiucheng Sun^*, Weiyu Dai, Mingyu Sun, Zeming Ren, Mingze Wang

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3957-3970, 2023, DOI:10.32604/cmc.2023.037254

Abstract In the traditional fringe projection profilometry system, the projector and the camera light center are both spatially virtual points. The spatial position relationships specified in the model are not easy to obtain, leading to inaccurate system parameters and affecting measurement accuracy. This paper proposes a method for solving the system parameters of the fringe projection profilometry system, and the spatial position of the camera and projector can be adjusted in accordance with the obtained calibration parameters. The steps are as follows: First, in accordance with the conversion relationship of the coordinate system in the calibration process, the calculation formula of… More >

Jia-Yu Liang¹, Hong-Bo Zhang^1,*, Qing Lei², Ji-Xiang Du³, Tian-Liang Lin⁴

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3243-3256, 2023, DOI:10.32604/iasc.2023.035812

Abstract Monocular 6D pose estimation is a functional task in the field of computer vision and robotics. In recent years, 2D-3D correspondence-based methods have achieved improved performance in multiview and depth data-based scenes. However, for monocular 6D pose estimation, these methods are affected by the prediction results of the 2D-3D correspondences and the robustness of the perspective-n-point (PnP) algorithm. There is still a difference in the distance from the expected estimation effect. To obtain a more effective feature representation result, edge enhancement is proposed to increase the shape information of the object by analyzing the influence of inaccurate 2D-3D matching on… More >

Sunyoung Bu¹, Suwon Lee^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 3083-3096, 2023, DOI:10.32604/cmes.2023.024460

Abstract Reconstructing a three-dimensional (3D) environment is an indispensable technique to make augmented reality and augmented virtuality feasible. A Kinect device is an efficient tool for reconstructing 3D environments, and using multiple Kinect devices enables the enhancement of reconstruction density and expansion of virtual spaces. To employ multiple devices simultaneously, Kinect devices need to be calibrated with respect to each other. There are several schemes available that calibrate 3D images generated from multiple Kinect devices, including the marker detection method. In this study, we introduce a markerless calibration technique for Azure Kinect devices that avoids the drawbacks of marker detection, which… More > Graphic Abstract

Tareq Alhmiedat^1,2,*, Ashraf M. Marei^1,2, Saleh Albelwi^1,2, Anas Bushnag², Wassim Messoudi², Abdelrahman Osman Elfaki^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2321-2344, 2023, DOI:10.32604/cmes.2023.025641

Abstract Agricultural projects in different parts of the world depend on underground water wells. Recently, there have been many unfortunate incidents in which children have died in abandoned underground wells. Providing topographical information for these wells is a prerequisite to protecting people from the dangers of falling into them, especially since most of these wells become buried over time. Many solutions have been developed recently, most with the aim of exploring these well areas. However, these systems suffer from several limitations, including high complexity, large size, or inefficiency. This paper focuses on the development of a smart exploration unit that is… More >

Hongtao Liu, Hongtao Jing, Zhixiong Tu^*, Shiyong Qin, Junhui Wei, Xiaotong Yu

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.7, pp. 1851-1862, 2023, DOI:10.32604/fdmp.2023.025015

Abstract Reservoirs characterized by high temperature, high-pressure, medium high cementation strength, low porosity, and low permeability, in general, are not affected by sand production issues. Since 2009, however, it is known that cases exists where sand is present and may represent a significant technical problem (e.g., the the Dina II condensate gas field). In the present study, the main factors affecting sand production in this type of reservoir are considered (mechanical properties, stress fields, production system, completion method and gas flow pattern changes during the production process). On this basis, a new liquid-solid coupled porous elasto-plastic 3D sand production model is… More >

Hiam Alquran^1,2, Yazan Al-Issa³, Mohammed Alslatie⁴, Isam Abu-Qasmieh¹, Amin Alqudah³, Wan Azani Mustafa^5,7,*, Yasmin Mohd Yacob^6,7

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1653-1671, 2023, DOI:10.32604/csse.2023.033861

Abstract Liver cancer is the second leading cause of cancer death worldwide. Early tumor detection may help identify suitable treatment and increase the survival rate. Medical imaging is a non-invasive tool that can help uncover abnormalities in human organs. Magnetic Resonance Imaging (MRI), in particular, uses magnetic fields and radio waves to differentiate internal human organs tissue. However, the interpretation of medical images requires the subjective expertise of a radiologist and oncologist. Thus, building an automated diagnosis computer-based system can help specialists reduce incorrect diagnoses. This paper proposes a hybrid automated system to compare the performance of 3D features and 2D… More >

V. P. Nithya^*, N. Mohanasundaram, R. Santhosh

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2601-2618, 2023, DOI:10.32604/csse.2023.030503

Abstract The prediction of mild cognitive impairment or Alzheimer’s disease (AD) has gained the attention of huge researchers as the disease occurrence is increasing, and there is a need for earlier prediction. Regrettably, due to the high-dimensionality nature of neural data and the least available samples, modelling an efficient computer diagnostic system is highly solicited. Learning approaches, specifically deep learning approaches, are essential in disease prediction. Deep Learning (DL) approaches are successfully demonstrated for their higher-level performance in various fields like medical imaging. A novel 3D-Convolutional Neural Network (3D-CNN) architecture is proposed to predict AD with Magnetic resonance imaging (MRI) data.… More >

Ruijun Liu¹, Haisheng Li^1,*, Zhihan Lv²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 985-1022, 2023, DOI:10.32604/cmes.2023.023154

Abstract To understand the current application and development of 3D modeling in Digital Twins (DTs), abundant literatures on DTs and 3D modeling are investigated by means of literature review. The transition process from 3D modeling to DTs modeling is analyzed, as well as the current application of DTs modeling in various industries. The application of 3D DTs modeling in the fields of smart manufacturing, smart ecology, smart transportation, and smart buildings in smart cities is analyzed in detail, and the current limitations are summarized. It is found that the 3D modeling technology in DTs has broad prospects for development and has… More >