Showing 15,181 - 15,200 results of 106,272 for search '(( 2 de decrease ) OR ( 5 ((point decrease) OR (((mean decrease) OR (a decrease)))) ))', query time: 1.77s Refine Results
  1. 15181
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  3. 15183

    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. …”
  4. 15184

    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. …”
  5. 15185

    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. …”
  6. 15186

    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. …”
  7. 15187

    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. …”
  8. 15188

    Image_1_Maternal exposure to air pollution alters energy balance transiently according to gender and changes gut microbiota.jpg by Olivia Pizetta Zordão (15181675)

    Published 2023
    “…This group showed a slight increase in food intake. In female offspring from FA/PM<sub>2.5</sub>, BW, and leptin levels were elevated. …”
  9. 15189

    DataSheet_1_Maternal exposure to air pollution alters energy balance transiently according to gender and changes gut microbiota.pdf by Olivia Pizetta Zordão (15181675)

    Published 2023
    “…This group showed a slight increase in food intake. In female offspring from FA/PM<sub>2.5</sub>, BW, and leptin levels were elevated. …”
  10. 15190

    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. 15191

    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). …”
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  14. 15194

    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. …”
  15. 15195

    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. …”
  16. 15196

    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. …”
  17. 15197

    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. …”
  18. 15198

    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. …”
  19. 15199

    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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