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    Fault Recognition Method and Application Based on Generative Adversarial Network by Shuiliang Luo, Yongmei Huang, Yun Su, Shengkui Wang, Qianqian Liu, Yingqiang Qi, Fuhao Chang

    Published 2025-06-01
    “…ABSTRACT In view of the limitation of generalization ability faced by deep learning in fault identification, especially in the case of complex underground geological conditions and variable seismic data characteristics, it is often ineffective to directly use the network based on synthetic data training for fault prediction of real data. …”
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    Assessment in education: Current trends, problems and contradictions (review of scientific publications) by I. B. Shmigirilova, A. S. Rvanova, O. V. Grigorenko

    Published 2021-06-01
    “…The variety of theoretical approaches to the interpretation of assessment forms, the ambiguous definition and use of terminology, the multiplicity of criteria-based assessment models, qualitatively different approaches to the development of criteria and the creation of assessment rubrics on their basis are sources of risks in the practice of educational assessment. …”
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    AI-Based Point Cloud Upsampling for Autonomous Driving Systems by Nicolás Salomón, Claudio A. Delrieux, Damián A. Morero, Leandro E. Borgnino

    Published 2025-05-01
    “…This work is based on 3 main axes: firstly, the analysis of available LiDAR data and its representation; secondly, the development and implementation of an interpolation technique based on 1D convolutional layers integrated with fully connected layers, in order to analyse data coming from a sliding window; and finally, the comparative evaluation of the results between different state-of-the-art interpolation techniques, using object detection networks in point clouds. …”
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