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Questions tagged [convolution]

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Cardinality vs width in the ResNext architecture

I was recently reading the paper Aggregated Residual Transformations for Deep Neural Networks. One thing the author mentions in Section (5.1) is that increasing the cardinality (or, the number of ...
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1answer
31 views

One-Dimensional Convolutional Neural Network

Can someone explain how 'One-Dimensional Convolutional Neural Network' works. I do understand the 2-D for image but for 1-D how is the filer created. is it fixed 1-D filter within a specific time ...
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1answer
19 views

How to choose the number of output channels in a convolutional layer?

I'm following a pytorch tutorial where for a tensor of shape [8,3,32,32], where 8 is the batch size, 3 the number of channels and 32 x 32, the pixel size, they define the first convolutional layer as ...
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11 views

Keras regularizers (kernel, bias and activity) vs tf.contrib.layers.apply_regularization

I have a DCGAN set up in tensorflow that is working well on the faces in the wild dataset. As an experiment, I tried using the same architecture in keras to better understand the difference in ...
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1answer
59 views

How can I detect blocks of text from scanned document images

ORIGINAL IMAGE: GOAL: I want to separate texts into individual paragraphs by placing bounding boxes over them (as shown above). I tried it do this via traditional computer vision approach using ...
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19 views

InvalidArgumentError: Conv2DCustomBackpropInput: input and out_backprop must have the same batch size

while trying to implement custom layers for GatedConv2D and GatedDeConv2D, i get this error. Generator: ...
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1answer
49 views

Application of Deep Reinforcement Learning

I'm new to deep learning, and especially to reinforcement learning. I would like to know if it's possible to predict which combination of hashtags (from a subset of chosen hashtags) would produce the ...
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13 views

Encoder Decoder Network Image Compression

Could you train an encoder decoder network to take an image in and attempt to recreate that image as an output. I am basically interested at looking at the intermediate feature vector representation ...
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1answer
23 views

Derivation of CNN math equations in Matrix format

I've gone through jefkine's website and Jae Seo's articles to get a hold of math behind the famous CNN architecture. Although I understand it in theory, I'm unable to implement in matrix format or to ...
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9 views

How to infer the convolutional structure for non-image data?

Imagine I have a large dataset of labeled images, and I process each image by mixing up the pixels. Each image is processed in exactly the same way (with a pixel-to-pixel table). Is it possible to ...
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1answer
21 views

Channels in convolutional layer

I usually see convolutions performed over all the channels of the input. For example a $3x3$ kernel is really a $3x3xN$ kernel for a an input with $N$ channels, thus resulting in a single output ...
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12 views

Transfer learning on a CNN for computer vision problems

Can a pretrained CNN for semantic segmentation be used for image classification, given the dataset is similar for both ? I am thinking that answer should be 'yes'. But when I tried replacing decoder ...
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What is the motivation for row-wise convolution and folding in Kalchbrenner et al. (2014)?

I was reading the paper by Kalchbrenner et al. titled A Convolutional Neural Network for Modelling Sentences and am struggling to understand their definition of convolutional layer. First, let's take ...
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1answer
64 views

Best CNN architecture for binary classification of small images with a massive dataset [closed]

The title has it all... Any tip is welcomed. Should I use a very deep convolutional neural network ? Use a large amount of filters ? Parallel layers ? Dataset examples: 1) "Good" 2) "Bad"
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1answer
13 views

How do I send the results of a convolutional layer and non-deep-learning features into a dense layer in Keras?

I understand that I can set up a convolutional network for 1-dimensional sequence/time series. ...
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1answer
39 views

How to label and detect the document text images

This is what I mean as document text image: I want to label the texts in image as separate blocks and my model should detect these labels as classes. NOTE: This is how the end result should be ...
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1answer
23 views

Mxnet deepdog (hot dog not hot dog) example - how does the network know it is classifying a hotdog

Looking at the mxnet documentation: https://gluon.mxnet.io/chapter08_computer-vision/fine-tuning.html It takes the pretrained squeenext1_1 weights, and sets imagenet_hotdog_index variable to 713. <...
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1answer
13 views

inner workings of Mobile-net resolution multiplier - what does it do?

i have a question concerning the way Mobile Net's resolution parameter works. From the article itself and from the blog posts on the topic (1, 2) I wasn't able to find an answer to my question. It is ...
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0answers
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Wavenet joint probability

As presented in the first article of Google Wavenet (https://arxiv.org/pdf/1609.03499.pdf) the model can approximate the joint probability of the whole sequence (raw audio waveform) using the chain ...
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1answer
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Approach fpr extracting/cropping features images using deeplearning and no annotations

Let's say I want to have a bunch of images of hats from videos. How would I priniciple build something that would learn to recognize, and crop or bound box hats? I heard you need a dataset with ...
2
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1answer
48 views

Comparison between addition and multiplication function in deep neural network?

I designed a specific Convolution Neural Network to study in the area of image processing. The network has a part that there are two tensors which have to be transformed into a tensor in order to be ...
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0answers
15 views

Can we do convolutions on binary mask inputs?

I am training a vehicle trajectory prediction algorithm using Deep MaxEnt Inverse Reinforcement Learning (https://arxiv.org/abs/1507.04888). My intention is to have as input to this algorithm a top-...
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20 views

Extract weight matrix of Convolutional Neural Network in MATLAB

I try to train Convolutional Neural Network via MATLAB and want to know the weight matrix and bias vector in each layer. The network works well but when I type "layer(2).Weights" it returns "[ ]". ...
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73 views

Changing padding values in Keras

What is the influence of changing the padding value with its borders, I might miss vocabulary because I can't find many papers about this alternative. Also I'd be interested in doing this in Keras, ...
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0answers
20 views

Are transposed convolutions computed using the Fast Fourier Transform?

In convolutional neural networks, transposed convolutions are represented by the transposed matrix which represents the convolution. But convolutions are not actually computed by creating this matrix, ...
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0answers
49 views

Training a convolutional neural network for image denoising in Matlab

first time posting in this stack exchange. I am currently trying to train CNNs to remove Poisson noise from images. The software I am using is Matlab 2018b, however the results I am getting are poor. ...
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0answers
19 views

Images Score Regression only regresses to the average of the target values

I have 700 3D images, each one having a target value. The target value distribution after standardizing looks as below After training, my validation set MSE (10% of data) does not go down and R2 ...
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1answer
51 views

Training a floor detection model: use full room images or only the cropped floor?

I'm trying to build a floor type image classification model.There's an open dataset called OpenSurfaces containing images segmented by the material type of every item appearing on a room. Something ...
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3answers
23 views

How to classify images Neural Network didn't trained to Understand

Let's say I trained a Convolution neural network to Identify Cats , Dogs and wolves . But suddenly I feed it pictures of rabbits and Lions. so how can I classify those as pictures as "Other" I ...
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1answer
16 views

How to add more emphasis on end columns in CNN?

I am using CNN for multivariate time series analysis. The input size is (batch_size, 500, 30) i.e 30 variables and 500 time steps. I want to put more emphasis on recent data and less on past data. ...
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1answer
20 views

Wrangling data for CNN

I am using convolutional nets for a physics application. I am trying to figure out how to structure my raw data as an image for input into the CNN. I have $N$ samples. Each sample consists of the ...
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0answers
245 views

Understanding how to use ConvLSTM for multistep ahead forecasting

I have a problem where I have transaction data for many banking accounts. The task is to train a model on historical debit/expense transactions and then forecast expense transactions for the next n ...
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2answers
141 views

Tensorflow (or Keras) vs. Pytorch vs. some other ML library for implementing a CNN [closed]

I am looking into implementing a convolutional neural network for a research problem. I've heard of deep learning libraries like Pytorch and Tensorflow and was hoping to get some additional ...
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1answer
36 views

How does Pooling Layer in CNN introduce invariance to other transformations besides translation

Here is a quote from deeplearningbook which I am trying to process. I am not sure what do they mean by this quote, can someone help me understand please? Pooling over spatial regions produces ...
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2answers
109 views

What is the purpose of a 1x1 convolutional layer?

SqueezeNet uses 1x1 convolutions. I try to understand it in this simple example: if the input is one MNIST digit, i.e. of shape 1x28x28x1 (I use Batch x Height x ...
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2answers
39 views

Subsequent convolution layers

Note: I've read How do subsequent convolution layers work? a few times, but it's still difficult to understand because of the parameters $k_1$, $k_2$, and many proposals (1, 2.1, 2.2) in the question. ...
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0answers
12 views

Test Loss plateau fast in Convolutional Neural Net

I have a 10k dataset of 1 channel 100X100pixels images with 31 classes. I set up a CNN with 3 convolution layers each followed by a batchnorm and a 2d pooling. I tried out several combinations of ...
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1answer
27 views

YOLO pretraining

I'm implementing YOLO network and have some questions. In the original paper the authors say: "For pretraining we use the first 20 convolutional layers from Figure 3 followed by a average-pooling ...
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1answer
61 views

YOLO layers size

According to the original paper, the input size of the YOLO network layer is 448x448x3 and after the filter (7x7x64-s-2) is applied the output shape is to be 221x221x192 as I suppose. Some sources ...
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1answer
34 views

Print the prediction of convolutional neural network

I have designed a convolutional neural network using tensorflow which looks as follows ...
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0answers
277 views

Why does Position Embeddings work?

In the papers "Convolutional Sequence to Sequence Learning" and "Attention Is All You Need", positions embeddings are simply added to the input words embeddings to give the model a sense of the order ...
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2answers
35 views

Extracting Useful features from large convolutional layers

I have been training a convolutional neural network on emotion detection. Now, I would like to extract features for my data to train an LSTM layer. In my case, the top convolutional layers in the ...
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0answers
15 views

Why is this convolution equation easier to apply than it's commutative counterpart?

The convolution is an operation on two functions of a real- valued argument. The convolution operation is typically denoted with an asterisk: s(t) = (x ∗ w)(t) ...
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1answer
444 views

Convolution and Cross Correlation in CNN

What would be the intuition behind using the convolution and cross correlation operation inside Convolutional Neural Networks? I am interested in putting together the theory from Digital Image ...
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1answer
119 views

Combining 2 Neural Networks

2 images as input, x1 and x2 and try to use convolution as a similarity measure. The idea is that the learned weights substitute more traditional measure of similarity (cross correlation, NN, ...). ...
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1answer
1k views

Keras Conv1D for simple data target prediction

I am trying to use conv1D layer from Keras for predicting Species in iris dataset (which has 4 numeric features and one categorical target). Following is my code: ...
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1answer
435 views

What is the difference between upsampling and bi-linear upsampling in a CNN?

I am trying to understand this paper and am unsure of what bi-linear upsampling is. Can anyone explain this at a high-level? https://arxiv.org/abs/1606.00915
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0answers
91 views

Preserve colour in convolutional autoencoder

at the moment i work with convolutional autoencoder and now I'am looking for paper or methods that adresses a colour preversation. Most of the AE paper use grayscale images and loss functions such as ...
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0answers
128 views

Transpose convolution math not working out

I was reading A Guide to Convolutional Arithmetic to understand Transpose Convolution as it is cited in Keras and Theano documentation. I am having trouble understanding the following two statements : ...
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2answers
52 views

Seemingly good results with training a CNN but bad when testing

I have an image classification task, and I am using Keras for a network with CNN layers, with what seems like good results in training, translates to poor performance in testing. Upon training, I ...