All Questions
29 questions
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37
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Training a transformer CNN for image output from scratch
I'm trying to train a Transformer-CNN model from scratch. The Transformer model is comparable to that of the ViViT model 2. The CNN is taking the output of the second (temporal) transformer and is ...
1
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22
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Transfer Learning - GoogLeNet - Training Times || Loss not converging || Pytorch
Hi Community and thanks in advance for the help.
I am working on transfer learning - specifically GoogLeNet model with the Food101 Dataset. Code is below. I think everything is in order from data ...
- 21
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62
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How to improve Accuracy on dermaMNIST dataset?
Unlike the regular MNIST which gets 97-99% with a fairly basic network, dermaMNIST gets training/validation stuck on 0.69. This tells me the model is underfitting. But, making it bigger seems to have ...
- 141
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22
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Training with few samples, dropping training loss but constant validation loss
I am training a resnet50-based model using transfer learning. My dataset has 10 classes and about 10 occurrences per class, so it is very small. The training loss is decreasing steadily to 0.07 for ...
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34
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Different results between training and evaluation phase on the same data
I have trained a CNN and in the training phase I obtained an accuracy of 36.5%.
If I call model.predict() on the same test data of the training phase I only obtain ...
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295
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How ca I reshape y_train , y_validation from train_generator?
I retrained ResNet-50 for iris flower classification in tensorflow using the following code:
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- 145
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1
answer
26
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Can we not backpropagate model
I saw a model based on CNN for question classification. The author said that they don't backpropagate gradient to embeddings. How this is possible to update network if you don't backpropagate please?
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- 231
1
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249
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Batch size and steps per epoch
My data size is 6011, which is a prime number, and therefore, the only batch size number that divides this data evenly is either 1 or 6011. However, I need the batch size to be 32, which means that ...
- 145
1
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246
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Q: Training a CNN-LSTM on video inputs
Hello everyone!
I implemented the following model, for action classification from videos, where each frame is 224x224x3, a video consists of ...
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1
answer
1k
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ValueError: Layer model expects 2 input(s), but it received 3 input tensors using generator
I am trying to fit a model using generator function and I get the following error:
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3
votes
2
answers
1k
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Troubles Training a Faster R-CNN RPN using a Resnet 101 backbone in Pytorch
Training Problems for a RPN
I am trying to train a network for region proposals as in the anchor box-concept from Faster R-CNN on the Pascal VOC 2012 training data.
I am using a pretrained Resnet 101 ...
- 119
9
votes
4
answers
3k
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Understanding how convolutional layers work
After working with a CNN using Keras and the Mnist dataset for the well-know hand written digit recognition problem, I came up with some questions about how the convolutional layer work. I can ...
2
votes
2
answers
467
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When a dataset is huge, what do you do to train with all the images on i t?
I'm using Python 3.7.7.
I'm trying to load a lot of NIFTI images using SimplyITK and Numpy from the [BraTS 2019 dataset][1].
This is the code I use to load the images into a numpy array.
...
- 279
0
votes
2
answers
183
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How to improve a CNN without changing the architecture?
I'm currently using an autoencoder CNN that's built upon the VGG-16 architecture that was designed by someone else. I want to replicate their results using their dataset first but I'm finding that:
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- 1
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2
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993
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CNN training on Different Datasets
I currently want to train a CNN but I have two small datasets that are slightly different because of the camera setup that captured the images. I'm interested in ultimately tuning the neural network ...
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