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Klasifikácia obrázkov pomocou CNN×Dilatovaná konvolučná neurónová sieť (Dilated CNN)×
OdborHlboké učenieHlboké učenie
RodinaMachine learningMachine learning
Rok vzniku20162016
TvorcaHe, K. et al. (ResNet); Tan, M. & Le, Q.V. (EfficientNet)van den Oord, A. et al.; Bai, S., Kolter, J.Z. & Koltun, V.
TypDeep convolutional neural network (supervised)Deep learning (dilated 1D convolutional network)
Pôvodný zdrojHe, K., Zhang, X., Ren, S. & Sun, J. (2016). Deep Residual Learning for Image Recognition. CVPR. DOI ↗van den Oord, A. et al. (2016). WaveNet: A Generative Model for Raw Audio. arXiv. link ↗
Ďalšie názvyCNN — Görüntü Sınıflandırma (ResNet / VGG / EfficientNet), convolutional neural network image classifier, deep image classification, ResNet / VGG / EfficientNetDilate Edilmiş CNN (WaveNet / TCN), WaveNet, Temporal Convolutional Network, TCN
Príbuzné55
ZhrnutieCNN image classification uses deep convolutional architectures such as ResNet (He et al., 2016), VGG and EfficientNet (Tan & Le, 2019) to sort images into categories. Stacked convolutional layers learn a hierarchy of visual features directly from pixels, and skip (residual) connections prevent the vanishing-gradient problem in very deep networks.A Dilated CNN is a one-dimensional convolutional network whose receptive field grows exponentially with depth, letting it model long-range structure in time series and audio signals. WaveNet (van den Oord et al., 2016) and the Temporal Convolutional Network of Bai, Kolter and Koltun (2018) are the prominent members of this family.
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ScholarGatePorovnať metódy: CNN Image Classification · Dilated CNN. Získané 2026-06-17 z https://scholargate.app/sk/compare