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  1. 61

    THE CURRENT STATE OF ARTIFICIAL INTELLIGENCE IN RADIOLOGY – A REVIEW OF THE BASIC CONCEPTS, APPLICATIONS, AND CHALLENGES by Mariana Yordanova

    Published 2025-03-01
    “…Deep learning, especially deep convolutional neural networks (CNNs), has become a prominent approach, mimicking brain functions to process images through multiple layers. …”
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  2. 62

    Object representations drive emotion schemas across a large and diverse set of daily-life scenes by Chuanji Gao, Susan Ajith, Marius V. Peelen

    Published 2025-05-01
    “…To explore this, we collected emotion ratings for 4913 daily-life scenes from 300 participants, and predicted these ratings from representations in deep neural networks and functional magnetic resonance imaging (fMRI) activity patterns in visual cortex. …”
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  3. 63

    Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

    Published 2025-01-01
    “…FGATN introduces three core innovations: (1) fuzzy membership functions to explicitly model uncertainty and imprecision in traffic features; (2) fuzzy similarity-based graph construction with adaptive edge pruning to build meaningful graph topologies that reflect real-world communication patterns; and (3) an attention-guided fuzzy graph convolution mechanism that dynamically prioritizes reliable and task-relevant neighbors during message passing. …”
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  4. 64

    GIRH-Unet: Improved Residual Tobacco Segmentation Algorithm Based on GhostNetV3-Unet by Jianhua Ye, Yunda Zhang, Pan Li, Ze Guo

    Published 2025-01-01
    “…Additionally, we optimize the residual modules and activation functions to enhance the extraction of detailed features and the deep transmission of information. …”
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  5. 65

    The triple-helix model as foundation of innovative entrepreneurial ecosystems by Klaus Bruno Schebesch, Horațiu Florin Șoim, Radu Lucian Blaga

    Published 2024-11-01
    “…As pointed out repeatedly, other important players are non-university research organizations with more focused goals (national labs, etc.), which should be explicitly accounted for. Another directions is distinguishing between support for (a) short-term high-tech, and for (b) longer term, deep-tech entrepreneurs. …”
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