Category : conv-neural-network

The topic of this project is Pothole Detection on Roads. In this project, this dataset (https://www.kaggle.com/sovitrath/road-pothole-images-for-pothole-detection) is used. First of all, all images in this dataset were separated into two classes as Negative(not pothole), and Positive(Contain Potholes). After that, all images were imported to code and a label is assigned to each image. These labels ..

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I am new to Pytorch, and I obtained a pertained model only (without model definition in python), and I can load it using command: mnet=torch.hub.load(…) which was successful, and I can pass input data to mnet. Now I hope to use the feature from the 3rd last layer as output, so I am doing this: ..

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I’m trying to predict future stock returns for 200 days ahead based on the past returns using neural networks. I’ve already implemented network which consists of several LSTM layers and it’s working ok: lstm2=Sequential([ LSTM(50,input_shape=[None,1],return_sequences=True), Dropout(0.2), LSTM(50,return_sequences=True), Dropout(0.2), LSTM(50), Dense(200) ]) However, when I try to stack a CONV1D layer on top of LSTM layers ..

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Firstly I was checking this notebook from Kaggle, and for some reason I couldn’t reproduce the Visualizing Filter Patterns of Convolution layers section of this notebook. I am getting this error: During handling of the above exception, another exception occurred: TypeError Traceback (most recent call last) TypeError: Cannot convert a symbolic Keras input/output to a ..

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