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  • Open Access

    REVIEW

    Trends in Event Understanding and Caption Generation/Reconstruction in Dense Video: A Review

    Ekanayake Mudiyanselage Chulabhaya Lankanatha Ekanayake1,2, Abubakar Sulaiman Gezawa3,*, Yunqi Lei1

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 2941-2965, 2024, DOI:10.32604/cmc.2024.046155

    Abstract Video description generates natural language sentences that describe the subject, verb, and objects of the targeted Video. The video description has been used to help visually impaired people to understand the content. It is also playing an essential role in devolving human-robot interaction. The dense video description is more difficult when compared with simple Video captioning because of the object’s interactions and event overlapping. Deep learning is changing the shape of computer vision (CV) technologies and natural language processing (NLP). There are hundreds of deep learning models, datasets, and evaluations that can improve the gaps in current research. This article… More >

  • Open Access

    ARTICLE

    Movement Function Assessment Based on Human Pose Estimation from Multi-View

    Lingling Chen1,2,*, Tong Liu1, Zhuo Gong1, Ding Wang1

    Computer Systems Science and Engineering, Vol.48, No.2, pp. 321-339, 2024, DOI:10.32604/csse.2023.037865

    Abstract Human pose estimation is a basic and critical task in the field of computer vision that involves determining the position (or spatial coordinates) of the joints of the human body in a given image or video. It is widely used in motion analysis, medical evaluation, and behavior monitoring. In this paper, the authors propose a method for multi-view human pose estimation. Two image sensors were placed orthogonally with respect to each other to capture the pose of the subject as they moved, and this yielded accurate and comprehensive results of three-dimensional (3D) motion reconstruction that helped capture their multi-directional poses.… More >

  • Open Access

    ARTICLE

    Isogeometric Analysis of Hyperelastic Material Characteristics for Calcified Aortic Valve

    Long Chen1, Ting Li1, Liang Liu1, Wenshuo Wang2,*, Xiaoxiao Du3, Wei Wang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2773-2806, 2024, DOI:10.32604/cmes.2024.046641

    Abstract This study explores the implementation of computed tomography (CT) reconstruction and simulation techniques for patient-specific valves, aiming to dissect the mechanical attributes of calcified valves within transcatheter heart valve replacement (TAVR) procedures. In order to facilitate this exploration, it derives pertinent formulas for 3D multi-material isogeometric hyperelastic analysis based on Hounsfield unit (HU) values, thereby unlocking foundational capabilities for isogeometric analysis in calcified aortic valves. A series of uniaxial and biaxial tensile tests is executed to obtain an accurate constitutive model for calcified active valves. To mitigate discretization errors, methodologies for reconstructing volumetric parametric models, integrating both geometric and material… More >

  • Open Access

    ARTICLE

    Learning Epipolar Line Window Attention for Stereo Image Super-Resolution Reconstruction

    Xue Li, Hongying Zhang*, Zixun Ye, Xiaoru Huang

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2847-2864, 2024, DOI:10.32604/cmc.2024.047093

    Abstract Transformer-based stereo image super-resolution reconstruction (Stereo SR) methods have significantly improved image quality. However, existing methods have deficiencies in paying attention to detailed features and do not consider the offset of pixels along the epipolar lines in complementary views when integrating stereo information. To address these challenges, this paper introduces a novel epipolar line window attention stereo image super-resolution network (EWASSR). For detail feature restoration, we design a feature extractor based on Transformer and convolutional neural network (CNN), which consists of (shifted) window-based self-attention ((S)W-MSA) and feature distillation and enhancement blocks (FDEB). This combination effectively solves the problem of global… More >

  • Open Access

    ARTICLE

    Advancing Wound Filling Extraction on 3D Faces: An Auto-Segmentation and Wound Face Regeneration Approach

    Duong Q. Nguyen1, Thinh D. Le3, Phuong D. Nguyen3, Nga T. K. Le2, H. Nguyen-Xuan3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 2197-2214, 2024, DOI:10.32604/cmes.2023.043992

    Abstract Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications. In this paper, we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network. Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions. To achieve accurate segmentation, we conducted thorough experiments and selected a high-performing model from the trained models. The selected model demonstrates exceptional segmentation performance for complex 3D facial wounds. Furthermore, based on the segmentation model, we propose an improved approach for extracting… More > Graphic Abstract

    Advancing Wound Filling Extraction on 3D Faces: An Auto-Segmentation and Wound Face Regeneration Approach

  • Open Access

    ARTICLE

    Histological Assessment of Bone Regeneration in the Maxilla with Homologous Bone Graft: A Feasible Option for Maxillary Bone Reconstruction

    Sergio Henrique Gonçalves Motta1, Ana Paula Ramos Soares1, Juliana Campos Hasse Fernandes2, Gustavo Vicentis Oliveira Fernandes2,3,*

    Journal of Renewable Materials, Vol.12, No.1, pp. 131-148, 2024, DOI:10.32604/jrm.2023.043940

    Abstract Bone biomaterials have been increasingly used to reconstruct maxillary atrophic ridges. Thus, the aim of this study was to evaluate bone reconstruction in the maxilla using a homologous cortico-cancellous FFB (lyophilized) graft and verify its reliability. Eight individuals were included from 2014 to 2018. The first surgery was performed to install homologous bone blocks in the maxilla. The period of the second intervention varied between 5 months and 15 days to 11 months (≈7.93 months). The biopsies were taken from the central region of the matured graft during the surgery for implant placement. All patients presented clinical and radiographic conditions… More >

  • Open Access

    ARTICLE

    Toward Improved Accuracy in Quasi-Static Elastography Using Deep Learning

    Yue Mei1,2,3, Jianwei Deng1,2, Dongmei Zhao1,2, Changjiang Xiao1,2, Tianhang Wang4, Li Dong5, Xuefeng Zhu1,6,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 911-935, 2024, DOI:10.32604/cmes.2023.043810

    Abstract Elastography is a non-invasive medical imaging technique to map the spatial variation of elastic properties of soft tissues. The quality of reconstruction results in elastography is highly sensitive to the noise induced by imaging measurements and processing. To address this issue, we propose a deep learning (DL) model based on conditional Generative Adversarial Networks (cGANs) to improve the quality of nonhomogeneous shear modulus reconstruction. To train this model, we generated a synthetic displacement field with finite element simulation under known nonhomogeneous shear modulus distribution. Both the simulated and experimental displacement fields are used to validate the proposed method. The reconstructed… More >

  • Open Access

    ARTICLE

    Enhanced 3D Point Cloud Reconstruction for Light Field Microscopy Using U-Net-Based Convolutional Neural Networks

    Shariar Md Imtiaz1, Ki-Chul Kwon1, F. M. Fahmid Hossain1, Md. Biddut Hossain1, Rupali Kiran Shinde1, Sang-Keun Gil2, Nam Kim1,*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2921-2937, 2023, DOI:10.32604/csse.2023.040205

    Abstract This article describes a novel approach for enhancing the three-dimensional (3D) point cloud reconstruction for light field microscopy (LFM) using U-net architecture-based fully convolutional neural network (CNN). Since the directional view of the LFM is limited, noise and artifacts make it difficult to reconstruct the exact shape of 3D point clouds. The existing methods suffer from these problems due to the self-occlusion of the model. This manuscript proposes a deep fusion learning (DL) method that combines a 3D CNN with a U-Net-based model as a feature extractor. The sub-aperture images obtained from the light field microscopy are aligned to form… More >

  • Open Access

    ARTICLE

    Modeling Method of C/C-ZrC Composites and Prediction of Equivalent Thermal Conductivity Tensor Based on Asymptotic Homogenization

    Junpeng Lyu1, Hai Mei1,2, Liping Zu1, Lisheng Liu1,2,*, Liangliang Chu1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 391-410, 2024, DOI:10.32604/cmes.2023.030614

    Abstract This article proposes a modeling method for C/C-ZrC composite materials. According to the superposition of Gaussian random field, the original gray model is obtained, and the threshold segmentation method is used to generate the C-ZrC inclusion model. Finally, the fiber structure is added to construct the microstructure of the three-phase plain weave composite. The reconstructed inclusions can meet the randomness of the shape and have a uniform distribution. Using an algorithm based on asymptotic homogenization and finite element method, the equivalent thermal conductivity prediction of the microstructure finite element model was carried out, and the influence of component volume fraction… More >

  • Open Access

    REVIEW

    Reconstruction of the Hindlimb Locomotion of Confuciusornis (Aves) and Its Implication for the Origin of Avian Flight

    Xinsen Wei1, Ying Guo1,2,*, Yan Zhao1

    Molecular & Cellular Biomechanics, Vol.20, No.2, pp. 49-61, 2023, DOI:10.32604/mcb.2023.041173

    Abstract As one of the most basal avian clades, the Confuciusornithids are ideal in revealing the early evolution of avian flight. Birds’ hindlimbs are functionally diverse and contain a wealth of information about their behavior. The hindlimb of Confuciusornis, however, has only been studied in detail in terms of functional morphology, and quantitative studies that directly assess locomotor ability are relatively lacking. This has led to certain controversies on the behavior of Confuciusornis. This paper reviews the debates over the life habits and take-off ability of Confuciusornis, which are closely related to their hindlimb function. Several methodologies adopted engineering techniques, including… More >

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