Tag ptn - Esta é a página 5 - GeneraCodice

How to backpropogate Convolution layer padding inputs with respect to output derivative

https://www.generacodice.com/pt/articolo/2688237/how-to-backpropogate-convolution-layer-padding-inputs-with-respect-to-output-derivative
  convolution  -  deep-learning  -  cnn
datascience.stackexchange datascience.stackexchange

PyTorchs ConvTranspose2d padding parameter

https://www.generacodice.com/pt/articolo/2688228/pytorchs-convtranspose2d-padding-parameter
  convolution  -  convnet  -  cnn  -  pytorch
datascience.stackexchange datascience.stackexchange

How to use a dataset with only one category of data

https://www.generacodice.com/pt/articolo/2687456/how-to-use-a-dataset-with-only-one-category-of-data
  keras  -  cnn
datascience.stackexchange datascience.stackexchange

Is there any possibility to apply deep dreaming in data augmentation?

https://www.generacodice.com/pt/articolo/2687010/is-there-any-possibility-to-apply-deep-dreaming-in-data-augmentation
  deep-learning  -  data-augmentation  -  cnn
datascience.stackexchange datascience.stackexchange

Understanding how convolutional layers work

https://www.generacodice.com/pt/articolo/2684278/understanding-how-convolutional-layers-work
  convolution  -  backpropagation  -  training  -  cnn
datascience.stackexchange datascience.stackexchange

For semantic sementation, why am I getting better loss values with binary cross entropy than dice coef?

https://www.generacodice.com/pt/articolo/2683406/for-semantic-sementation-why-am-i-getting-better-loss-values-with-binary-cross-entropy-than-dice-coef
  image-segmentation  -  loss-function  -  cnn  -  semantic-segmentation
datascience.stackexchange datascience.stackexchange

Improving misclassification for one class in a multi-class classification task

https://www.generacodice.com/pt/articolo/2683170/improving-misclassification-for-one-class-in-a-multi-class-classification-task
  deep-learning  -  accuracy  -  multilabel-classification  -  keras  -  cnn
datascience.stackexchange datascience.stackexchange

When a dataset is huge, what do you do to train with all the images on i t?

https://www.generacodice.com/pt/articolo/2683118/when-a-dataset-is-huge-what-do-you-do-to-train-with-all-the-images-on-i-t
  dataset  -  training  -  cnn
datascience.stackexchange datascience.stackexchange

Is Flatten() layer in keras necessary?

https://www.generacodice.com/pt/articolo/2683043/is-flatten-layer-in-keras-necessary
  neural-network  -  convnet  -  keras  -  cnn  -  transfer-learning
datascience.stackexchange datascience.stackexchange

Is it possible to reuse my CNN trained model over a new dataset with different number of classes?

https://www.generacodice.com/pt/articolo/2682982/is-it-possible-to-reuse-my-cnn-trained-model-over-a-new-dataset-with-different-number-of-classes
  classification  -  tensorflow  -  keras  -  cnn  -  machine-learning-model
datascience.stackexchange datascience.stackexchange
Resultados encontrados: 1034
scroll top