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  • Open Access

    ARTICLE

    An Interactive Collaborative Creation System for Shadow Puppets Based on Smooth Generative Adversarial Networks

    Cheng Yang1,2, Miaojia Lou2,*, Xiaoyu Chen1,2, Zixuan Ren1

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4107-4126, 2024, DOI:10.32604/cmc.2024.049183 - 20 June 2024

    Abstract Chinese shadow puppetry has been recognized as a world intangible cultural heritage. However, it faces substantial challenges in its preservation and advancement due to the intricate and labor-intensive nature of crafting shadow puppets. To ensure the inheritance and development of this cultural heritage, it is imperative to enable traditional art to flourish in the digital era. This paper presents an Interactive Collaborative Creation System for shadow puppets, designed to facilitate the creation of high-quality shadow puppet images with greater ease. The system comprises four key functions: Image contour extraction, intelligent reference recommendation, generation network, and… More >

  • Open Access

    ARTICLE

    Shadow Extraction and Elimination of Moving Vehicles for Tracking Vehicles

    Kalpesh Jadav1, Vishal Sorathiya1,*, Walid El-Shafai2, Torki Altameem3, Moustafa H. Aly4, Vipul Vekariya5, Kawsar Ahmed6, Francis M. Bui6

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2009-2030, 2023, DOI:10.32604/cmc.2023.043168 - 29 November 2023

    Abstract Shadow extraction and elimination is essential for intelligent transportation systems (ITS) in vehicle tracking application. The shadow is the source of error for vehicle detection, which causes misclassification of vehicles and a high false alarm rate in the research of vehicle counting, vehicle detection, vehicle tracking, and classification. Most of the existing research is on shadow extraction of moving vehicles in high intensity and on standard datasets, but the process of extracting shadows from moving vehicles in low light of real scenes is difficult. The real scenes of vehicles dataset are generated by self on… More >

  • Open Access

    ARTICLE

    Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network

    Lilan Zou1, Bo Liang1, Xu Cheng2, Shufa Li1,*, Cong Lin1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2641-2659, 2023, DOI:10.32604/cmes.2023.028037 - 03 August 2023

    Abstract Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment. In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment, we proposed a more effective and robust target detection framework based on deep learning, which can make full use of the acoustic shadow information in the forward-looking sonar images to assist underwater target detection. Firstly, the weighted box fusion method is adopted to generate a fusion box by weighted… More > Graphic Abstract

    Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network

  • Open Access

    ARTICLE

    Atrous Convolution-Based Residual Deep CNN for Image Dehazing with Spider Monkey–Particle Swarm Optimization

    CH. Mohan Sai Kumar*, R. S. Valarmathi

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1711-1728, 2023, DOI:10.32604/iasc.2023.038113 - 21 June 2023

    Abstract Image dehazing is a rapidly progressing research concept to enhance image contrast and resolution in computer vision applications. Owing to severe air dispersion, fog, and haze over the environment, hazy images pose specific challenges during information retrieval. With the advances in the learning theory, most of the learning-based techniques, in particular, deep neural networks are used for single-image dehazing. The existing approaches are extremely computationally complex, and the dehazed images are suffered from color distortion caused by the over-saturation and pseudo-shadow phenomenon. However, the slow convergence rate during training and haze residual is the two… More >

  • Open Access

    ARTICLE

    Influence of Wind Turbine Structural Parameters on Wind Shear and Tower Shadow Effect

    Yajing Zhang1, Chaoyang Song2, Zhiguo Li2,*

    Energy Engineering, Vol.120, No.2, pp. 501-510, 2023, DOI:10.32604/ee.2022.021423 - 28 November 2022

    Abstract To overcome the problems of natural decreases in power quality, and to eliminate wind speed fluctuation due to wind shear and tower shadow effect arising from wind turbine structural parameters, an improved prediction model accounting for the dual effect of wind shear and tower shadow is, in this paper, built. Compared to the conventional prediction model, the proposed model contains a new constraint condition, which makes the disturbance term caused by the tower shadow effect always negative so that the prediction result is closer to the actual situation. Furthermore, wind turbine structural parameters such as More > Graphic Abstract

    Influence of Wind Turbine Structural Parameters on Wind Shear and Tower Shadow Effect

  • Open Access

    ARTICLE

    Improved Multileader Optimization with Shadow Encryption for Medical Images in IoT Environment

    Mesfer Al Duhayyim1,*, Mohammed Maray2, Ayman Qahmash2, Fatma S. Alrayes3, Nuha Alshuqayran4, Jaber S. Alzahrani5, Mohammed Alghamdi2,6, Abdullah Mohamed7

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3133-3149, 2023, DOI:10.32604/cmc.2023.032740 - 31 October 2022

    Abstract Nowadays, security plays an important role in Internet of Things (IoT) environment especially in medical services’ domains like disease prediction and medical data storage. In healthcare sector, huge volumes of data are generated on a daily basis, owing to the involvement of advanced health care devices. In general terms, health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty diagnosis. At the same time, it is also significant to maintain the delicate contents of health care images during reconstruction stage. Therefore, an encryption system is… More >

  • Open Access

    ARTICLE

    Ghost-RetinaNet: Fast Shadow Detection Method for Photovoltaic Panels Based on Improved RetinaNet

    Jun Wu, Penghui Fan, Yingxin Sun, Weifeng Gui*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1305-1321, 2023, DOI:10.32604/cmes.2022.020919 - 31 August 2022

    Abstract Based on the artificial intelligence algorithm of RetinaNet, we propose the Ghost-RetinaNet in this paper, a fast shadow detection method for photovoltaic panels, to solve the problems of extreme target density, large overlap, high cost and poor real-time performance in photovoltaic panel shadow detection. Firstly, the Ghost CSP module based on Cross Stage Partial (CSP) is adopted in feature extraction network to improve the accuracy and detection speed. Based on extracted features, recursive feature fusion structure is mentioned to enhance the feature information of all objects. We introduce the SiLU activation function and CIoU Loss… More >

  • Open Access

    ARTICLE

    Implementation of a solar model and shadow plotting in the context of a 2D GIS

    A validation based on radiometric measurements

    Thomas Leduc, Xenia Stavropulos-Laffaille, Ignacio Requena-Ruiz

    Revue Internationale de Géomatique, Vol.31, No.2, pp. 241-263, 2022, DOI:10.3166/rig31.241-263

    Abstract The adaptation of public spaces to episodes of intense heat is now a major challenge for cities. With this in mind, this article presents a contribution aimed at delineating and handling the shadows on the ground or in a horizontal plane at a given height, whether it comes from buildings, street furniture or the tree cover. After a comparison with shadows obtained via two reference tools, we present two urban sites that mix shadows of different origins and, in addition, different indicators. The results of the simulations are compared with pyranometric surveys carried out on More >

  • Open Access

    ARTICLE

    Indoor Scene Splicing Based on Genetic Algorithm and ORB

    Tao Zhang1,*, Yi Cao2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1677-1685, 2022, DOI:10.32604/iasc.2022.027082 - 24 March 2022

    Abstract The images generated by the image stitching algorithm have false shadow and poor real-time performance, and are difficult to maintain visual consistency. For this reason, a panoramic image stitching algorithm based on genetic algorithm is proposed. First, the oriented fast and rotated brief (ORB) algorithm is used to quickly perform detection and description of feature, then the initial feature point pairs are extracted according to the Euclidean distance for feature point rough matching, the parallelism of genetic algorithm is used to optimize the feature point matching performance. Finally, the PROSAC algorithm is used to remove More >

  • Open Access

    ARTICLE

    Analysis and Modeling of Propagation in Tunnel at 3.7 and 28 GHz

    Md Abdus Samad1,2, Dong-You Choi1,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3127-3143, 2022, DOI:10.32604/cmc.2022.023086 - 07 December 2021

    Abstract In present-day society, train tunnels are extensively used as a means of transportation. Therefore, to ensure safety, streamlined train operations, and uninterrupted internet access inside train tunnels, reliable wave propagation modeling is required. We have experimented and measured wave propagation models in a 1674 m long straight train tunnel in South Korea. The measured path loss and the received signal strength were modeled with the Close-In (CI), Floating intercept (FI), CI model with a frequency-weighted path loss exponent (CIF), and alpha-beta-gamma (ABG) models, where the model parameters were determined using minimum mean square error (MMSE)… More >

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