Questions tagged [convolution]

For use when discussing the commutative and linear, but not associative operator interpreted on functions and distributions.

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Help needed implementing Convolutional Sequence-to-Sequence Network

I am trying to build convolutional Sequence-to-Sequence network that takes inputs (satellite images) and predicts the next sequence of images. As a result, we can then predict the weather. I have ...
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wavenet structure explanation

I am a beginner in deep learning and recently I am trying to understand the structure of Wavenet. (for more information, please refer to the paper http://sergeiturukin.com/2017/03/02/wavenet.html) ...
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Why use separable convolutions on one channel input?

I'm currently working on the Text Classification Guide from Google. During step 4, they create a CNN with separable convolutions for use with word embeddings: <...
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18 views

Why do we use a softmax activation function in Convolutional Autoencoders?

I have been working on an image segmentation project where I have created a convolutional autoencoder. I saw this image and implemented it using Keras. At the output layer, the author has used the ...
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11 views

1D convolution for uni-variate data

Every one. I have EEG dataset with 80 subjects, 3072 data points and 100 trials. This a univariate data, it mean there is only one channel. I am confused how to feed this data to convolution neural ...
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Backpropagation from a fully-connected layer to a pooling or convolution layer

I've a problem where I currently try to wrap my head around. Consider a CNN with a single convolution layer and a fully-connected layer. During the forward pass, the input is processed through the ...
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+50

Tensorflow F-RCNN first stage input and output strides

Trying to optimize performances on Tensorflow's faster_rcnn_resnet50 (from the model zoo), I'm currently working on understanding the full .config file they provide, and I'm having a hard time with ...
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When is bias set to False?

I have been working with DC-GAN to generate pairs of images based on WGAN paper. For which I referred fastai notebook on WGAN where the bias in the network has been set to False. Jeremy Howard in his ...
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36 views

Map predictions to real text

I have read the paper "Learning to Read by Spelling" by Gutpa et al. They present a method for visual text recognition without using any paired supervisory data. In chapter 4 they describe how to ...
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31 views

Understanding Faster R-CNN

I'm having some trouble understanding the way the Faster R-CNN algorithm works. Specifically, the way the authors describe the concept of anchors. In their paper from here they describe anchors in ...
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In a CNN do filters that account for depth do so for just the initial input, or for a layers with any depth?

For example, if you have an input of an image of size 100x100x3 (where 3 is the RGB of the image), then put it through a conv layer that results in an output of <...
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23 views

conv2d function in pytorch

I'm trying to use the function torch.conv2d from Pytorch but can't get a result I understand... Here is a simple example where the kernel (filt) is the same size ...
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I am building a gesture recognition system using video data from ConGD Dataset and am not able to create the 5D array,as input to the network

I need a 5D input for my network using ConvLSTM and 3D-CNN. Converting the videos to an array of videos would contain a 5D array (Num of examples, Num of frames, FrameWidth, FrameHeight, NoOfChannels),...
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254 views

What is fractionally-strided convolution layer?

In paper Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs, in Section 3.4, it said Since, the aim of this work is to estimate high-resolution and high-quality density maps,...
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55 views

Anyone have fruit disease dataset? [closed]

I am doing a project on fruit disease recognition and classification. Anyone have an existing dataset of fruit diseases? Can you help me to find one?
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117 views

How to calculate receptive field size for -ception model?

I have a full convolution model like this: ...
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27 views

Struggling to understand GCN (Graph Convolutional Networks)

Although I've worked with CNN's for over a year, I am struggling to understand how GCN's work. I've read several papers, and I find myself out of my depth when they talk about Chebyshev polynomials or ...
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How is R-FCN faster than FRCNN?

During my first pass through the architecture for R-FCN, I believed that it was because their region proposal network generated regions of interest without performing the "small network slide" over ...
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Dimension of feature vectors for classification task in the DCGAN paper

I am trying to implement one of the section in the DCGAN paper (https://arxiv.org/pdf/1511.06434.pdf) i.e. Using the Discriminator network trained on ImageNet-1k as a feature extractor to classify ...
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21 views

Decovolution function

I have an image (for example (7x7x3) and a filter (3x3x3)). I convolved the image with the filter and it became a (3x3) output. If I want to do the inverse operation and want it to become the image ...
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How to compute mAP?

I would like to compute mAP. I detect only 1 class. I know should create two array. Presicion array and recall array and plot Precision/Recall Curve (PR Curve). Max of Groud-truth bounding boxes: 4 ...
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67 views

CNN output shape explanation

I have the following sequential model: ...
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28 views

Reconstructing input image from layers of a CNN

I've been trying to implement neural style transfer as described in this paper here According to the paper, we can visualise the information at different processing stages in the CNN by ...
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1answer
60 views

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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182 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
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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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71 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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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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61 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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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
41 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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1answer
92 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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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
458 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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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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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
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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
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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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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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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 ...
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1answer
76 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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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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40 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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126 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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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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199 views

Training a convolutional neural network for image denoising in Matlab

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. I have followed the steps provided in the ...
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25 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
150 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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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 ...