Showing 161 - 180 results of 12,457 for search '(coevolutionary OR convolutional)', query time: 0.12s Refine Results
  1. 161

    Segmentation for mammography classification utilizing deep convolutional neural network by Dip Kumar Saha, Tuhin Hossain, Mejdl Safran, Sultan Alfarhood, M. F. Mridha, Dunren Che

    Published 2024-12-01
    “…Methods Recently, the transformer model has emerged as a method for overcoming the constraints of convolutional neural networks (CNN). Thus, our primary goal was to determine how well an improved transformer model could distinguish between benign and malignant breast tissues. …”
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  2. 162

    An Efficient Group Convolution and Feature Fusion Method for Weed Detection by Chaowen Chen, Ying Zang, Jinkang Jiao, Daoqing Yan, Zhuorong Fan, Zijian Cui, Minghua Zhang

    Published 2024-12-01
    “…This model introduces plug-and-play modules: (1) The Efficient Group Convolution (EGC) module leverages convolution kernels of various sizes combined with group convolution techniques to significantly reduce computational cost. …”
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  3. 163

    A New Support Vector Machine Based on Convolution Product by Wei-Chang Yeh, Yunzhi Jiang, Shi-Yi Tan, Chih-Yen Yeh

    Published 2021-01-01
    “…The support vector machine (SVM) and deep learning (e.g., convolutional neural networks (CNNs)) are the two most famous algorithms in small and big data, respectively. …”
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  4. 164

    Learning Transferable Convolutional Proxy by SMI-Based Matching Technique by Wei Jin, Nan Jia

    Published 2020-01-01
    “…By minimizing an objective function of SMI, classification error, and manifold regularization, we learn the convolutional networks of both source and target domains. …”
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    Digital-analog quantum convolutional neural networks for image classification by Anton Simen, Carlos Flores-Garrigos, Narendra N. Hegade, Iraitz Montalban, Yolanda Vives-Gilabert, Eric Michon, Qi Zhang, Enrique Solano, José D. Martín-Guerrero

    Published 2024-12-01
    “…An architecture that combines nontrainable quantum kernels and standard convolutional neural networks is used to classify realistic medical images, from breast cancer and pneumonia diseases, with a significantly reduced number of parameters. …”
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    Article
  9. 169

    Improved Hierarchical Convolutional Features for Robust Visual Object Tracking by Jinping Sun

    Published 2021-01-01
    “…Thus, to improve the tracking performance and robustness, an improved hierarchical convolutional features model is proposed into a correlation filter framework for visual object tracking. …”
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    Convolution Properties for Some Subclasses of Meromorphic Functions of Complex Order by M. K. Aouf, A. O. Mostafa, H. M. Zayed

    Published 2015-01-01
    “…Making use of the operator Lυ for functions of the form fz=1/z+∑k=1∞akzk-1, which are analytic in the punctured unit disc U∗={z:z∈C and 0<|z|<1}=U∖{0}, we introduce two subclasses of meromorphic functions and investigate convolution properties, coefficient estimates, and containment properties for these subclasses.…”
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    Bernoulli Identities and Combinatoric Convolution Sums with Odd Divisor Functions by Daeyeoul Kim, Yoon Kyung Park

    Published 2014-01-01
    “…We study the combinatoric convolution sums involving odd divisor functions, their relations to Bernoulli numbers, and some interesting applications.…”
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  20. 180