Showing 14,081 - 14,100 results of 101,229 for search '(( 5 wt decrease ) OR ( 5 ((((ng decrease) OR (a decrease))) OR (mean decrease)) ))', query time: 1.75s Refine Results
  1. 14081
  2. 14082
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  4. 14084

    Training set data expansion. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  5. 14085

    Structural plane recognition effect. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  6. 14086

    Structural plane classification. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  7. 14087

    Mixup data expansion. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  8. 14088

    Marking example. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  9. 14089
  10. 14090

    Neuroreceptor kinetics in rats repeatedly exposed to quinpirole as a model for OCD by Stijn Servaes (6433580)

    Published 2019
    “…Subsequently, sagittal slides were made of the CP in the right hemisphere and a staining was done with the D2R, mGluR5 and GLT-1 antibody to visualize the corresponding receptor.…”
  11. 14091

    Data_Sheet_1_Determining 5HT7R’s Involvement in Modifying the Antihyperalgesic Effects of Electroacupuncture on Rats With Recurrent Migraine.pdf by Lu Liu (171341)

    Published 2021
    “…<p>Electroacupuncture (EA) is widely used in clinical practice to relieve migraine pain. 5-HT<sub>7</sub> receptor (5-HT<sub>7</sub>R) has been reported to play an excitatory role in neuronal systems and regulate hyperalgesic pain and neurogenic inflammation. 5-HT<sub>7</sub>R could influence phosphorylation of protein kinase A (PKA)- or extracellular signal-regulated kinase<sub>1</sub><sub>/</sub><sub>2</sub> (ERK<sub>1</sub><sub>/</sub><sub>2</sub>)-mediated signaling pathways, which mediate sensitization of nociceptive neurons via interacting with cyclic adenosine monophosphate (cAMP). …”
  12. 14092
  13. 14093

    Amygdala voxel correlations with ACC whose values <i>decrease</i> as symptoms of post-combat emotional distress increase. by Tom Brashers-Krug (762715)

    Published 2015
    “…Threshold for significance was a <i>z</i>-score < -5.39. Coronal slices through the brain at y = 4, 2, 0, -2, -4, -6, and -8 mm showing the amygdala bilaterally. …”
  14. 14094

    ACC voxel correlations with amygdala whose values <i>decrease</i> as symptoms of post-combat emotional distress increase. by Tom Brashers-Krug (762715)

    Published 2015
    “…Threshold for significance was a <i>z</i>-score < -5.39. Only values within the ACC ROI are shown. …”
  15. 14095

    Drill image dataset for training part II. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  16. 14096

    U<sup>2</sup>-Net network structure diagram [8]. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  17. 14097

    RSU-7 structure diagram [8]. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
  18. 14098

    Drill image dataset for training part I. by Qingjun Yu (1649473)

    Published 2024
    “…Based on the PyTorch deep learning framework, the initial U<sup>2</sup>-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”
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