Showing 61 - 76 results of 76 for search 'Gympie~', query time: 1.32s Refine Results
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    Seismic microzonation studies in the Southern part of Progo River, special Region of Yogyakarta, Indonesia by Ghina Bani Azifah, Teuku Faisal Fathani, Hendy Setiawan

    Published 2025-02-01
    “…Results Results indicated that the highest value of PGA was obtained using the deterministic GMPE NGA West 2 weighted attenuation equation, which varied from 0.475 to 0.549 g. …”
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    Théorie de la régulation et histoire du droit :un croisement fertile by Samuel Klebaner

    Published 2022-08-01
    “…The methodologies developed in the Max Planck Institute of Frankfurt am Main (MPIeR) analyze the emergence and the performativity of law. …”
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    Non-Destructive Estimation of Paper Fiber Using Macro Images: A Comparative Evaluation of Network Architectures and Patch Sizes for Patch-Based Classification by Naoki Kamiya, Kosuke Ashino, Yasuhiro Sakai, Yexin Zhou, Yoichi Ohyanagi, Koji Shibazaki

    Published 2024-11-01
    “…We experimentally classified three types of paper fibers, namely, kozo, mitsumata, and gampi. During the experiments, patch sizes of 500, 750, and 1000 pixels were evaluated and their impact on classification accuracy was analyzed. …”
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    Spectral Domain Optical Coherence Tomography Assessment of Macular and Optic Nerve Alterations in Patients with Glaucoma and Correlation with Visual Field Index by Alessio Martucci, Nicola Toschi, Massimo Cesareo, Clarissa Giannini, Giulio Pocobelli, Francesco Garaci, Raffaele Mancino, Carlo Nucci

    Published 2018-01-01
    “…Sectorial thickness values of each retinal layer and of the optic nerve were measured using SD-OCT Glaucoma Module Premium Edition (GMPE) software. Each parameter was compared between the groups, and the layers and sectors with the best area under the receiver operating characteristic curve (AUC) were identified. …”
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    Proposing Algorithm Using YOLOV4 and VGG-16 for Smart-Education by Phat Nguyen Huu, Khang Doan Xuan

    Published 2021-01-01
    “…In the first step, we use YOLOV4 (Kumar et al. 2020; Canu, 2020) to recognize equations and letters associated with the VGG-16 network (Simonyan and Zisserman, 2015) to classify them. We then used the SymPy model to solve the equations in the second step. …”
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