يعرض 141 - 160 نتائج من 18,267 نتيجة بحث عن '(( significant source decrease ) OR ( significant attention dataset ))', وقت الاستعلام: 0.60s تنقيح النتائج
  1. 141
  2. 142

    S3 Dataset - حسب Shiqi Huang (4640158)

    منشور في 2022
  3. 143

    S1 Dataset - حسب Shiqi Huang (4640158)

    منشور في 2022
  4. 144

    S2 Dataset - حسب Shiqi Huang (4640158)

    منشور في 2022
  5. 145

    S7 Dataset - حسب Shiqi Huang (4640158)

    منشور في 2022
  6. 146

    S5 Dataset - حسب Shiqi Huang (4640158)

    منشور في 2022
  7. 147

    S6 Dataset - حسب Shiqi Huang (4640158)

    منشور في 2022
  8. 148

    S4 Dataset - حسب Shiqi Huang (4640158)

    منشور في 2022
  9. 149
  10. 150

    Structure of the SE attention mechanism. حسب Haixia Liu (764025)

    منشور في 2025
    "…To address this issue, this study innovatively combines multi-scale feature extraction (MSFE) and attention feature fusion (AFF). After optimization, the multi-scale recursive attentional feature fusion block (MSRAFFB) and MSRAFFB Network (MSRAFFB-Net) application algorithms are proposed. …"
  11. 151

    Attention weight analysis. حسب Yuhao Gong (4788654)

    منشور في 2025
    "…Using a dataset of 6,608 students, TGEL-Transformer achieved RMSE = 1.87 and R<sup>2</sup> = 0.75, outperforming existing methods with statistically significant improvements (p < 0.001) ranging from 1.1% against recent state-of-the-art models to 5.6% against transformer baselines. …"
  12. 152
  13. 153

    Paired t-test on the KvasirV1 dataset. حسب Poonam Sharma (467670)

    منشور في 2025
    "…Two publicly available datasets, Kather and KvasirV1, were utilized for model training and testing. …"
  14. 154

    Results comparison on the KvasirV1 dataset. حسب Poonam Sharma (467670)

    منشور في 2025
    "…Two publicly available datasets, Kather and KvasirV1, were utilized for model training and testing. …"
  15. 155
  16. 156

    The heatmap of the self-attention on UTD-MHAD. حسب Dongwei Xie (4874992)

    منشور في 2025
    "…<div><p>3D skeleton-based human activity recognition has gained significant attention due to its robustness against variations in background, lighting, and viewpoints. …"
  17. 157
  18. 158
  19. 159

    S1 Dataset - حسب Li Zhang (8200)

    منشور في 2024
  20. 160