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  1. 461
    “…Using simulations we identify a critical value of the Reynolds number for cavitation inception that scales inversely with the order parameter of the fluid. …”
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    Hydrodynamic cavitation in Stokes flow of anisotropic fluids
  2. 462
    “…Three transferred models, InceptionV3, ResNet50, and Xception, a CNN model with three convolutional layers (CNN3), and traditional machine learning-based model with hand-crafted features were developed for differentiating benign and malignant tumors from BUS data. …”
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    Comparison of Transferred Deep Neural Networks in Ultrasonic Breast Masses Discrimination
  3. 463
    por Kunicki, Michal
    Publicado 2019
    “…The PDS is powered continuously by the AC voltage with its relative level of 1.3 of the inception voltage (U(i)) within 168 h. UHF signals generated by the continuously occurred SD within 168 h are registered. …”
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    Variability of the UHF Signals Generated by Partial Discharges in Mineral Oil
  4. 464
    “…Ongoing studies are critical to our understanding of the role of the airway microbiome in asthma inception and exacerbation. • Synergistic interactions between underlying allergy and virus infections play an important mechanistic role in asthma inception and exacerbation, and are an important therapeutic target. • Novel therapies are needed to prevent and treat virus-induced wheezing and asthma exacerbations.…”
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    Infections and Asthma: Impact on the Natural History of Asthma
  5. 465
    “…In this paper, we propose a Mini-Inception-Residual-Dense (MIRD) network named MIRD-Net to deal with this problem. …”
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    MIRD-Net for Medical Image Segmentation
  6. 466
    por Zak, Matthew, Krzyżak, Adam
    Publicado 2020
    “…We implemented three deep convolutional neural networks (VGG16, ResNet-50, and InceptionV3) pre-trained on the ImageNet dataset and assesed them in lung disease classification tasks using transfer learning approach. …”
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    Classification of Lung Diseases Using Deep Learning Models
  7. 467
    “…The generated samples are visualized for qualitative evaluation. The inception score (IS) and Fréchet inception distance (FID) are adopted to measure the performance of the model for quantitative assessment. …”
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    Improving Multi-Agent Generative Adversarial Nets with Variational Latent Representation
  8. 468
    “…We also observed that the transfer approach enabled to improve the accuracy of the Inception ResNet 3D version up to 18% with respect to the score of the 3D approach alone.…”
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    3D Convolutional Neural Networks Initialized from Pretrained 2D Convolutional Neural Networks for Classification of Industrial Parts
  9. 469
    “…In addition, HRGAN outperforms other existing models in terms of the Inception score, one of the conventional methods to evaluate GANs. …”
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    HRGAN: A Generative Adversarial Network Producing Higher-Resolution Images than Training Sets
  10. 470
    “…The symposium will be presented in the following heads- 1.Background and Inception- Dr Dinesh Kataria; 2.Training of workforce- Dr Prerna Kukreti; 3.Service Delivery- Dr Bhavuk Garg.…”
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    Mental Health Support Group: A model to create Mental Health Workforce for Health Care
  11. 471
    por Guanglong, Bao, Qian, Gao
    Publicado 2022
    “…The model is designed based on Inception V3 that is proposed by Google. The innovation lies in that transfer learning which is integrated into Inception V3 to improve the generalization ability. …”
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    Correlation Analysis between the Emotion and Aesthetics for Chinese Classical Garden Design Based on Deep Transfer Learning
  12. 472
    “…The accuracy rate of the proposed SDCNet is 96.91% for the multiclassification of skin cancer whereas, the accuracy rates for Resnet 50, Alexnet, Vgg19 and Inception-v3 are 95.21%, 93.14%, 94.25% and 92.54%, respectively. …”
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    SCDNet: A Deep Learning-Based Framework for the Multiclassification of Skin Cancer Using Dermoscopy Images
  13. 473
    “…Four different network architectures (CNN, Resnet152, MobileNet, and Inception V3) were used to build the algorithm. The algorithm was able to predict the parameters for a given requirement. …”
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    Predicting the Optimal Input Parameters for the Desired Print Quality Using Machine Learning
  14. 474
    “…The sensitivity was as follows: InceptionV3 (0.507 ± 0.060), ResNet101 (0.680 ± 0.056), and VGG19 (0.747 ± 0.056). …”
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    Identification of tophi in ultrasound imaging based on transfer learning and clinical practice
  15. 475
    “…The highest accuracy was achieved using the InceptionResNetV2 model, with an impressive accuracy of 98.73%. …”
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    The classification of the bladder cancer based on Vision Transformers (ViT)
  16. 476
    “…Our data also indicate that the Inception module-based CNN performs better than the AlexNet-based CNN (Inception module-based CNN reached an accuracy of 99.25%). …”
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    Multimodal MRI-based classification of migraine: using deep learning convolutional neural network
  17. 477
    “…The diagnostic accuracy of the pretrained Inception‐V3 and AlexNet DCNNs was tested on ADC maps and PCT(1)W images separately. …”
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    Accuracy of deep learning to differentiate the histopathological grading of meningiomas on MR images: A preliminary study
  18. 478
    por Head, Martin J.
    Publicado 2021
    “…MIS 19c begins ~ 791–787.5 ka, includes full interglacial conditions which lasted for ~ 8–12.5 kyr, and ends with glacial inception at ~ 774–777 ka. This inception has left an array of climatostratigraphic signals close to the Early–Middle Pleistocene boundary. …”
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    Review of the Early–Middle Pleistocene boundary and Marine Isotope Stage 19
  19. 479
    “…In contrast, for segmented CXRs, InceptionV3 outperformed using the original CXR dataset and achieved sensitivities of 96.94%, 79.68%, and 90.26% for classifying COVID-19, MERS, and SARS images, respectively. …”
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    Deep Learning for Reliable Classification of COVID-19, MERS, and SARS from Chest X-ray Images
  20. 480
    “…Using the generalized estimating equation models with panel data of monthly and yearly payment per physician, the payment trend since the inception of the Open Payments Database and during the early stage of the COVID-19 pandemic were evaluated. …”
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    Trend in industry payments to infectious disease physicians in the United States: a seven-year analysis of nonresearch payments from the Open Payments Database between 2014 and 2020
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