Showing 261 - 280 results of 711 for search 'Generalized nets', query time: 0.04s Refine Results
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    COVID-19 Deep Learning Prediction Model Using Publicly Available Radiologist-Adjudicated Chest X-Ray Images as Training Data: Preliminary Findings by Mohd Zulfaezal Che Azemin, Radhiana Hassan, Mohd Izzuddin Mohd Tamrin, Mohd Adli Md Ali

    Published 2020-01-01
    “…With a limited number of publicly available COVID-19 chest X-ray images, the generalization and robustness of deep learning models to detect COVID-19 cases developed based on these images are questionable. …”
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    Article
  3. 263

    Hypothesis on the role of cholesterol crystals in spontaneously ruptured aortic plaques: Potential triggers for inflammation and systemic effects by Chikao Yutani, Hirotaka Noda, Nobuzo Iwa, Sei Komatsu, Satoru Takahashi, Yoshiharu Higuchi, Kazuhisa Kodama

    Published 2025-03-01
    “…Spontaneously ruptured aortic plaques (SRAPs) are frequently observed via non-obstructive general angioscopy (NOGA) in patients with or suspected coronary artery disease. …”
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    Measurement-Based Prediction of mmWave Channel Parameters Using Deep Learning and Point Cloud by Hang Mi, Bo Ai, Ruisi He, Anuraag Bodi, Raied Caromi, Jian Wang, Jelena Senic, Camillo Gentile, Yang Miao

    Published 2024-01-01
    “…Second, based on a classic point cloud classification model (PointNet), we propose a novel regression PointNet model applied to channel parameter prediction. …”
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    QR-DeepONet: resolve abnormal convergence issue in deep operator network by Jie Zhao, Biwei Xie, Xingquan Li

    Published 2024-01-01
    “…Theoretical analysis indicates that the generation error of DeepONet should decrease as the basis dimension increases, thus providing a systematic way to reduce its generalization errors (GEs) by varying the network hyperparameters. …”
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  19. 279

    Non-intrusive load monitoring based on time-enhanced multidimensional feature visualization by Tie Chen, Yimin Yuan, Jiaqi Gao, Shinan Guo, Pingping Yang

    Published 2025-02-01
    “…Furthermore, utilizing transfer learning, the model trained and tested on the PLAID dataset was further tested on the WHITED dataset to increase the model’s universality and generalization ability, showing significant effects in identifying loads with similar V–I trajectories and multiple states.…”
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  20. 280

    Deep learning in defects detection of PV modules: A review by Katleho Masita, Ali Hasan, Thokozani Shongwe, Hasan Abu Hilal

    Published 2025-01-01
    “…Despite achieving high accuracy, challenges such as the need for large datasets and model generalization across different PV modules and environmental conditions remain. …”
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