Showing 1,301 - 1,320 results of 15,418 for search '"learning"', query time: 0.08s Refine Results
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    Active learning in undergraduate classroom dental education- a scoping review. by Arnaldo Perez, Jacqueline Green, Mohammad Moharrami, Silvia Gianoni-Capenakas, Maryam Kebbe, Seema Ganatra, Geoff Ball, Nazlee Sharmin

    Published 2023-01-01
    “…<h4>Introduction</h4>Previous reviews on active learning in dental education have not comprehensibly summarized the research activity on this topic as they have largely focused on specific active learning strategies. …”
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    Analysis of Physical Human–Robot Interaction for Motor Learning with Physical Help by Shuhei Ikemoto, Takashi Minato, Hiroshi Ishiguro

    Published 2008-01-01
    “…The aim of this research is to develop a motor learning system that uses physical help from a human helper. …”
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    Adaptive Image Denoising Method Based on Diffusion Equation and Deep Learning by Shaobin Ma, Lan Li, Chengwen Zhang

    Published 2022-01-01
    “…Combined with batch standardization and residual learning technology, the image denoising network model based on deep residual learning of the convolutional network is designed with better denoising performance. …”
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    AN AUTOMATED SKIN DISEASE DIAGNOSTIC SYSTEM BASED ON DEEP LEARNING MODEL by LAWRENCE OMOTOSHO, KEHINDE SOTONWA, BENJAMIN ADEGOKE, OLUWASHINA OYENIRAN, JOSHUA OYENIYI

    Published 2022-01-01
    Subjects: “…dermatology, artificial intelligence, deep learning, AlexNet…”
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    Federated learning based reference evapotranspiration estimation for distributed crop fields. by Muhammad Tausif, Muhammad Waseem Iqbal, Rab Nawaz Bashir, Bayan AlGhofaily, Alex Elyassih, Amjad Rehman Khan

    Published 2025-01-01
    “…Efforts have been made to simplify the (ETo) estimation using machine learning models. The existing approaches are limited to a single specific area. …”
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    DETECTION OF KERATOCONUS DISEASE DEPENDING ON CORNEAL TOPOGRAPHY USING DEEP LEARNING by Aseel Abdulhasan Hashim, Mahdi Mazinani

    Published 2025-02-01
    “…The proposed system works on three stages: pre-processing, feature extraction, and classification with machine learning algorithms including NB, KNN, ADA, DT, and CNN deep learning. …”
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