I try to create a model by concatenating 2 models together. The models I want to use, shall handle time series, and I’m experimenting with Conv1D layers. As these have an 3D input shape batch_shape + (steps, input_dim) and the Keras TimeseriesGenerator is providing such, I’m happy being able to make use of it when handling single head models. This
Tag: conv-neural-network
Traing a CNN using Prelu activation function
I’m trying to train the model using prelu activation function, but I get the following error I’m using the below-mentioned code, kindly let me know how do I correct it. Answer Your tensor input is wrong. You need to set it up like this way Full working code
TensorFlow CNN Incompatible Shapes: 4D input shape
I have sample data in the form: Data[n][31][31][5][2] with: “[n]” being the sample “[31][31]” being the array of data points “[5]” being the number of bits within that data point and “[2]” being one-hot encoding of the bits (eg a bit of 1 would be [1, 0] and a zero [0, 1]) The output is intended to either be a
Pytorch: 1D target tensor expected, multi-target not supported
I want to train a 1D CNN on time series. I get the following error message 1D target tensor expected, multi-target not supported Here is the code with simulated data corresponding to the structures of my data as well as the error message Error message: What am I doing wrong? Answer You are using nn.CrossEntropyLoss as the criterion for your
Why do sometimes CNN models predict just one class out of all others?
I am relatively new to the deep learning landscape, so please don’t be as mean as Reddit! It seems like a general question so I won’t be giving my code here as it doesn’t seem necessary (if it is, here’s the link to colab) A bit about the data: You can find the original data here. It is a downsized
I created a CIFAR10 dataset learning model using a CNN model. Why is there an error?
I created a CIFAR10 dataset learning model using a CNN model. Why is there an error? How should I fix it? I did it in Google colab environment. This error occurred to me ValueError Traceback (most recent call last) in () /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs) ValueError: in user code: Thank you for your answering. Answer I think that your labels
max pooling across one dimension using keras
I have implemented a 3D-convolution neural network. The shape of my input is (500,10,4,1). I only want to convolve in first dimension such that it is ‘fully connected’ in second and third dimension in a way. So I use kernel size of (30,10,4). So far it’s fine. But when I do max pooling it reduces the second and third dimension
How to save trained images without a burden on network
I am training a convolutional neural network in pytorch and want to save trained images. I append each trained image in a data loader loop to save all the trained images into numpy file (train_pred in …
My deep learning model is not training. How do I make it train?
I’m fairly new to Keras, please excuse me if I made a fundamental error. So, my model has 3 Convolutional (2D) layers and 4 Dense Layers, interspersed with Dropout Layers. I am trying to train a Regression Model using images. X_train.shape = (5164, 160, 320, 3) y_train.shape = (5164) When I try to run this model, the training loss decreases
How get the predicted label from a Convolution Neural Net in image classification
I have built a CIFAR-10 image classification model with Convolution Neural Net or CNNs. The model fully completed and has got around 59% accuracy, but my problem is that how to get the predicted label from the model. it can predict these classes(10): What I’m trying to say is that, for example we give the model a image of a