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  • Open Access

    ARTICLE

    Multi-Objective Image Optimization of Product Appearance Based on Improved NSGA-Ⅱ

    Yinxue Ao1, Jian Lv1,*, Qingsheng Xie1, Zhengming Zhang2

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3049-3074, 2023, DOI:10.32604/cmc.2023.040088

    Abstract A second-generation fast Non-dominated Sorting Genetic Algorithm product shape multi-objective imagery optimization model based on degradation (DNSGA-II) strategy is proposed to make the product appearance optimization scheme meet the complex emotional needs of users for the product. First, the semantic differential method and K-Means cluster analysis are applied to extract the multi-objective imagery of users; then, the product multidimensional scale analysis is applied to classify the research objects, and again the reference samples are screened by the semantic differential method, and the samples are parametrized in two dimensions by using elliptic Fourier analysis; finally, the fuzzy dynamic evaluation function is… More >

  • Open Access

    ARTICLE

    Appearance Based Dynamic Hand Gesture Recognition Using 3D Separable Convolutional Neural Network

    Muhammad Rizwan1,*, Sana Ul Haq1,*, Noor Gul1,2, Muhammad Asif1, Syed Muslim Shah3, Tariqullah Jan4, Naveed Ahmad5

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 1213-1247, 2023, DOI:10.32604/cmc.2023.038211

    Abstract Appearance-based dynamic Hand Gesture Recognition (HGR) remains a prominent area of research in Human-Computer Interaction (HCI). Numerous environmental and computational constraints limit its real-time deployment. In addition, the performance of a model decreases as the subject’s distance from the camera increases. This study proposes a 3D separable Convolutional Neural Network (CNN), considering the model’s computational complexity and recognition accuracy. The 20BN-Jester dataset was used to train the model for six gesture classes. After achieving the best offline recognition accuracy of 94.39%, the model was deployed in real-time while considering the subject’s attention, the instant of performing a gesture, and the… More >

  • Open Access

    ARTICLE

    Effects of High Temperature and Strong Light Combine Stress on Yield and Quality of Early Indica Rice with Different Amylose Content during Grout Filling

    Xiaofeng Ai1, Ruoyu Xiong1, Xueming Tan1, Haixia Wang1, Jun Zhang2, Yongjun Zeng1, Xiaohua Pan1, Qinghua Shi1, Taoju Liu1, Yanhua Zeng1,*

    Phyton-International Journal of Experimental Botany, Vol.91, No.6, pp. 1257-1267, 2022, DOI:10.32604/phyton.2022.018328

    Abstract High temperature (HT) accompanied with strong light (SL) often occurs in early indica rice production during grout filling stage in southern China, which accelerates grain ripening. Two indica rice cultivars with different amylose content (Zhongjiazao17, ZJZ17, high amylose content; Xiangzaoxian45, XZX45, low amylose content) were grown under control (CK), HT, and HT+SL conditions during grout filling to determine the effects on grain yield and quality of rice. The results showed that compared with CK, HT and HT+SL significantly reduced the 1000-grain weight and filled grain rate whether in high or low amylose content early indica rice cultivars during grout filling,… More >

  • Open Access

    ARTICLE

    Multi-Modality Video Representation for Action Recognition

    Chao Zhu1, Yike Wang1, Dongbing Pu1,Miao Qi1,*, Hui Sun2,*, Lei Tan3,*

    Journal on Big Data, Vol.2, No.3, pp. 95-104, 2020, DOI:10.32604/jbd.2020.010431

    Abstract Nowadays, action recognition is widely applied in many fields. However, action is hard to define by single modality information. The difference between image recognition and action recognition is that action recognition needs more modality information to depict one action, such as the appearance, the motion and the dynamic information. Due to the state of action evolves with the change of time, motion information must be considered when representing an action. Most of current methods define an action by spatial information and motion information. There are two key elements of current action recognition methods: spatial information achieved by sampling sparsely on… More >

  • Open Access

    ARTICLE

    Robust Visual Tracking Models Designs Through Kernelized Correlation Filters

    Detian Huang1, Peiting Gu2, Hsuan-Ming Feng3,*, Yanming Lin1, Lixin Zheng1

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 313-322, 2020, DOI:10.31209/2019.100000105

    Abstract To tackle the problem of illumination sensitive, scale variation, and occlusion in the Kernelized Correlation Filters (KCF) tracker, an improved robust tracking algorithm based on KCF is proposed. Firstly, the color attribute was introduced to represent the target, and the dimension of target features was reduced adaptively to obtain low-dimensional and illumination-insensitive target features with the locally linear embedding approach. Secondly, an effective appearance model updating strategy is designed, and then the appearance model can be adaptively updated according to the Peak-to-Sidelobe Ratio value. Finally, the low-dimensional color features and the HOG features are utilized to determine the target state… More >

  • Open Access

    ARTICLE

    Semi-automatic Segmentation of Multiple Sclerosis Lesion Based Active Contours Model and Variational Dirichlet Process

    Foued Derraz1, Laurent Peyrodie2, Antonio PINTI3, Abdelmalik Taleb-Ahmed3, Azzeddine Chikh4, Patrick Hautecoeur5

    CMES-Computer Modeling in Engineering & Sciences, Vol.67, No.2, pp. 95-118, 2010, DOI:10.3970/cmes.2010.067.095

    Abstract We propose a new semi-automatic segmentation based Active Contour Model and statistic prior knowledge of Multiple Sclerosis (MS) Lesions in Regions Of Interest (RIO) within brain Magnetic Resonance Images(MRI). Reliable segmentation of MS lesion is important for at least three types of practical applications: pharmaceutical trails, making decision for drug treatment, patient follow-up. Manual segmentation of the MS lesions in brain MRI by well qualified experts is usually preferred. However, manual segmentation is hard to reproduce and can be highly cost and time consuming in the presence of large volume of MRI data. In other hand, automated segmentation methods are… More >

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