Showing 1 - 20 results of 27 for search '(( ct ((largest decrease) OR (larger decrease)) ) OR ( learning setup decrease ))', query time: 0.40s Refine Results
  1. 1
  2. 2
  3. 3
  4. 4
  5. 5

    Model and learning rule. by Janis Keck (21587252)

    Published 2025
    “…<b>(C), (D)</b> Invariance of learning rules with respect to temporal order. We plot synaptic weight change of a single synapse in a setup with a single pre- and postsynaptic neuron, respectively. …”
  6. 6
  7. 7
  8. 8

    Data Sheet 1_Correlation analysis of osteoporosis and vertebral endplate defects using CT and MRI imaging: a retrospective cross-sectional study.pdf by Song Hao (5700608)

    Published 2025
    “…</p>Methods<p>Computed tomography (CT), magnetic resonance imaging (MRI), bone mineral density (BMD) and other relevant imaging data, as well as age, sex, body mass index (BMI), and degree of low back pain data, were retrospectively analysed. …”
  9. 9

    LSTM model. by Longfei Gao (698900)

    Published 2025
    “…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
  10. 10

    CNN model. by Longfei Gao (698900)

    Published 2025
    “…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
  11. 11

    Ceramic bearings. by Longfei Gao (698900)

    Published 2025
    “…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
  12. 12

    Geometric contact arc length model. by Longfei Gao (698900)

    Published 2025
    “…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
  13. 13

    Indentation fracture mechanics model. by Longfei Gao (698900)

    Published 2025
    “…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
  14. 14

    Grinding particle cutting machining model. by Longfei Gao (698900)

    Published 2025
    “…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
  15. 15

    Three stages of abrasive cutting process. by Longfei Gao (698900)

    Published 2025
    “…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
  16. 16

    CNN-LSTM action recognition process. by Longfei Gao (698900)

    Published 2025
    “…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
  17. 17
  18. 18

    Video 1_Evaluating robotic assistance on the learning curve and efficiency of mandibular angle ostectomy: an animal model study.mov by Wenqing Han (12609103)

    Published 2024
    “…The study found that robotic assistance could decrease the risk of complications and enhance surgical outcomes. …”
  19. 19

    Data Sheet 1_Evaluating robotic assistance on the learning curve and efficiency of mandibular angle ostectomy: an animal model study.pdf by Wenqing Han (12609103)

    Published 2024
    “…The study found that robotic assistance could decrease the risk of complications and enhance surgical outcomes. …”
  20. 20

    Nyamsuren, I., Mitchell, E., and Tsay, J. (April 27 - May 2, 2025), <i>Learning Sign Language with Real-Time Kinematic Feedback</i> [Poster Presentation]. The Annual Meeting of the... by Indranil Nyamsuren (21498833)

    Published 2025
    “…However, after familiarizing themselves with the game during training, experts adapted their signing to be more accurate and easier for the webcam setup to recognize. These preliminary results suggest that our machine learning algorithm can recognize signs quite accurately.…”