Questions tagged [convnet]

For questions regarding "Convolutional Neural Networks" (CNN)

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Tensorflow.js - CNN/or autoencoder denoiser architecture?

I am new to machine learning. I have 10,000 examples of 128x256 array of values 0.0-1.0. Each example consists of a pair of a clean example and the other with noise added. I am aiming to train a CNN / ...
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How to approach a spatio-temporal forecasting?

I am dealing with a Spatio-temporal forecasting problem similar to the one dealing with the NYC Taxi Demand Prediction. This case is a good example since it has been already covered in different ...
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How to use pre-trained word2vec model generated by Gensim with Convolutional neural networks (CNN)

I have generated a pre-trained word2vec model using the Gensim framework (https://radimrehurek.com/gensim/auto_examples/index.html#documentation). The dataset has 507 sentiments(sentences) which are ...
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Problems with shape of Conv1D on Keras

I have some problems with layers construction on Keras. I explain the whole problem: I have a feature matrix, with dimensions: 2023 (rows) x 65 (features); I tried to build a CNN, with Conv1D as ...
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2 answers
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Are there studies which examine dropout vs other regularizations?

Are there any papers published which show differences of the regularization methods for neural networks, preferably on different domains (or at least different datasets)? I am asking because I ...
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How do subsequent convolution layers work?

This question boils down to "how do convolution layers exactly work. Suppose I have an $n \times m$ greyscale image. So the image has one channel. In the first layer, I apply a $3\times 3$ ...
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1 answer
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Can the size of a pooling layer be learned?

As far as I understood it, the pooling layer doesn't learn anything. It has several parameters, most important its pool_size and ...
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268 votes
11 answers
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What are deconvolutional layers?

I recently read Fully Convolutional Networks for Semantic Segmentation by Jonathan Long, Evan Shelhamer, Trevor Darrell. I don't understand what "deconvolutional layers" do / how they work. The ...
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6 votes
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Convolutional neural network for sparse one-hot representation

I have some basic features which I encoded in a one-hot vector. Length of the feature vector equals to 400. It is sparse. I saw that conv nets is applied to a dense feature vectors. Is there any ...
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6 votes
1 answer
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Neural Network Golf: smallest network for a certain level of performance

I am interested in any data, publications, etc about what is the smallest neural network that can achieve a certain level of classification performance. By small I mean few parameters, not few ...
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42 votes
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How to prepare/augment images for neural network?

I would like to use a neural network for image classification. I'll start with pre-trained CaffeNet and train it for my application. How should I prepare the input images? In this case, all the ...
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