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Questions tagged [convolutional-neural-networks]

For questions about convolutional neural networks, also known as CNN or ConvNet.

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CNN Translation invariant or translation equivariant?

I am trying to understand this post, but get confused by the definitions and the differences. Not sure what's definition of equivariant? If I remove all the pooling layers from CNN it will make the ...
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Point Cloud Alignment using a Neural Network?

Having two point clouds, the second being a transformation of the first, how could I utilize a neural network in order to solve the pose (transformation in terms of x, y, z, rx, ry, rz) of the second ...
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Simple weakly supervised Object localizetion using keras. How to visualize the results?

I am following this link : Weakly-supervised-object-localization to create heatmap of the region in an image where the CNN looks to identify the class. As per the above mentioned repository , ...
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25 views

Does changing the order of the convolution layers in a CNN have any impact?

Could changing the order of convolution layers in a CNN improve accuracy or training time?
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Use Image data from Drive to Colab for Image Augmentation

I am working on CNN. I have saved images in drive to do image augmentation in keras, I have used method (.flow_from_directory(directory)) Since it require directory path. I have mounted drive and give ...
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Do bounding boxes increase accuracy in and of themselves?

Say I have a standard image classification problem (ie: CNN is shown a single image and predicts a single classification for it). If I were to use bounding boxes to surround the target image (ie: ...
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24 views

How should the values of the filters of a CNN change?

I wrote a convolutional neural network for the MNIST dataset with Numpy from scratch. I am currently trying to understand every part and calculation. But one thing I noticed was the "just positive" ...
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36 views

How to identify the areas to reduce over fitting?

I am trying classify CIFAR10. The CNN that I generated over fits when the accuracy reaches ~77%. The code and the plot is given below. I tried DropOut, Batch Normalization and L2 Regularization. But ...
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how to benefit from previous training weights in training again to increase accuracy?

I have trained a modified VGG classification CNN, with random initialized weights; therefor the validation accuracy was not high enough for me to accept (around 66%). now using the weights resulted ...
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35 views

Variational Autoencoder task for better feature extraction

I have a CNN with the regression task of a single scalar. I was wondering if an additional task of reconstructing the image (used for learning visual concepts), seen in a DeepMind presentation with ...
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48 views

How do I choose the number of neurons in the fully-connected layer before the softmax layer?

I am solving a classification problem with CNN. The number of classes is 5. How can I decide the number of neurons in the FC layer before the softmax layer? Is it $N * 5$, where $N$ is the number of ...
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My own CNN model have dW of 500 and have numpy runtime error

I am implementing a CNN from scratch and it sometimes gave me numpy overflow error. I then debug the network and found that the gradients of the first 2 layers is around 500 to -500. The gradients of ...
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Confused about group convolution

I think I don't understand group convolutions well. Say you have 2 groups. This means that the number of parameters would be reduced in half. So assuming u have an image and 100 channels, with a ...
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Is it possible to make a 'forked path' neural network?

I want to make a network, specifically a CNN for image recognition, that takes an input, processes it the same way for several layers, and then at some point splits before coming to two different ...
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33 views

What are the key differences between cellular neural network and convolutional neural network?

What are the key differences between cellular neural networks and convolutional neural networks in terms of working principle, implementation, potential performance, and applicability?
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40 views

Why are not validation accuracy and loss as smooth as train accuracy and loss?

I am training a modified VGG16 network for classification (adding 0.5 dropout after each of the last FC layers). In the following plot I am training for a small number of epochs as an example, and it ...
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How do I denoize a microscopic image?

I'm working in a computer vision project, where the goal is to detect some specific parasites, but now that I have the images, I noticed that they have a watermark that specifies the microscope ...
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Using the cloud service to trasform a picture using a neural algorithm?

yesterday I tried to transform a picture in the artistic style using CNNs based on A Neural Algorithm of Artistic Style by Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge using a recent Torch ...
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27 views

When is bias values updated in back propagation?

I am new to deep learning. I have doubts on modifying bias values during back propagation. My doubts are Does the back propagation algorithm modifies the weigh values and bias values in the same pass?...
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CNN doesn't learning simple geometric patterns

It must be a very stupid question, but since I have not such sufficient know ledge storage and having no more time to search the answer of it, I have to put it here to ask for help. I generated a ...
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27 views

CNN output generally has more than one category in one-hot categorization?

I'm a bit of a CNN newbie, and I'm trying to train one to image classify pictures of pretty similar looking particles. I'm making the inputs and labels by hand from a set of 48x48 grayscale images, ...
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32 views

Algorithms to indentify people in pictures without using face recognition

There are lot of researches about face detection in pictures, but is it the only way one can say "this person I'm looking for is here in this picture"? Aren't there algorithms that you can provide ...
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24 views

Extending a neural network to classify new objects

Suppose a model M classifies apples and oranges. Can M be extended to classify a third class of objects, e.g., pears, such that ...
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Back propagation on Flatten Layer in CNN

I am making a NN library without any other external NN lib and is implementing the Flatten layer. I know the forward implementation of flatten layer but is the backward just reshaping it or not? If ...
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Which neural network to use for mapping a vector of size m to a vector of size n, where n >> m?

I am trying to solve a mapping problem on a grid (100x100) where I have few points, say 10, where I know the values of a tensor $\boldsymbol{M}$. I have a scalar field, $v$, which is related to the ...
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31 views

Double Convolution Layers in Yolov3

Lately, I have been working on yolov3 and have been trying to train it on x-ray images to detect a fracture. However, I have decided that I would want to increase the number of convolution layers for ...
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What is a simplified way to explain why the AI researchers Bengio, Hinton, and Lecun, won the 2019 Turing Award?

The Turing award is sometimes called Computer Sceince's Nobel Prize. This year's award goes to Bengio, Hinton, and LeCun for their work on artificial neural networks. The actual work contributed by ...
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Classification of classes within meta-classes

TLTR: I'm developing a CNN for a classification task. The data contains multiple classes some of which are very similar to each other and I know these meta-classes. In such a situation is it a good ...
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Convolutional Sequence to Sequence Learning: Training vs Generation

I am struggling to understand the use of the Convolutional Sequence to Sequence (Conv-Seq2Seq) model. The image below is take directly from the paper and is the nearly canonical diagram of the ...
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how to add the pool4 to the 2 x conv7 in FCN-16s using keras?

Now I'm using tensorflow.keras to implement the FCN-16s, this picture may be different with others, you should focus this it add ...
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One dimension deconvolutions or fully connected layers?

I’ve created a variational autoencoder to encode 1-dimensional arrays. The encoding is done through 3 1d-convolutional layers. Then, after the sampling trick, I reconstruct the series using 3 fully ...
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2answers
47 views

Detecting abnormalities in x-rays while taking into account demographics of a patient -automated

This is my first post so please forgive me for any mistakes. I am working on an object detection algorithm that can detect abnormalities in an x-ray. As a prototype, I will be using yolov3 (more ...
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Image-Specific Class Saliency Visualisation

In the paper "Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps", https://arxiv.org/abs/1312.6034, at part 3, there is a first-order Taylor expansion(...
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How do I improve accuracy and know when to stop training?

I am training a modified VGG-16 to classify crowd density (empty, low, moderate, high). 2 dropout layers were added at the end on the network each one after one of the last 2 FC layers. network ...
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Can we compare MAE MSE results with categorical_crossentropy?

can i compare MAE and MSE loss results of a regression CNN with categorical_crossentropy loss of a classification CNN if they both have similar tasks? is yes how to?
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How to Add Spp(Spatial Pyramid pool) layer to CNN network?

i create A model based on ELA [error level Analysis] for image forgery detection i use the following code : ...
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1answer
40 views

How to chose dense layer size?

I am fine-tuning a VGG16 model on 20 classes with 500k images I was wondering how do you chose the size of the dense layer (the one before the prediction layer which has a size 20). I would prefer not ...
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Very Large 3D Input Size

I would like to use a 3D convolutional network on a 2000x2000x2000 volume for segmentation. I know I can break the volume into chunks that can fit in VRAM, but I was wondering if there was a way to ...
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how to work with multi-labels or two inputs and a output

I’m in this problem and haven’t found a sound solution to it. Been like 20 days now. I have a dataset that looks like this: ...
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metrics evaluation multiclass classification

I am working on intent classification task (chatbot engine), 2k sentences, 24 classes. Major class is composed of about 150 sentences, minor class of about 35 sentences, the others are more or less ...
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26 views

Is making lot of 1 versus other model efficient?

I've got classification problem on image, I have 10 classes and when I fine tuned my model on it (I tried VGG, Xception, resnet etc) I have approximatly 83% validation accuracy. I was wondering if ...
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34 views

Why don't we perform classification of crowd density?

For the case of crowd density estimation using CNN, using datasets like shanhaiTech or UCF, why there hasn't been attempts to tackle this type of task as a classification problem? All current papers I'...
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any workaround to manipulate/transform recurrent CNN for sentence classification?

I learned how to build recurrent cnn model for text classification and sketched out my initial implementation. However, I am wondering how to transform recurrent <...
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1answer
54 views

Why doesn't my image classification network get better with training?

I am attempting to train a network to do something I thought would be a relatively simple case to learn with: identify whether the back of a scanned vintage postcard has one of 'no postage stamp', a '...
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Maximum number of nodes for CNN for mobile phones

I am building a mobile camera app that needs to show a real time preview of the processed image. So i was thinking of reducing the image size to 100 x 100. But as for the weights and number of layers. ...
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41 views

How to reduce over-fitting on training set?

Currently I'm feeding spectrogram of audio to the CNN with 3 convolution. Each convolution is followed by a max pool of filter size 2. First -> 5x5x4 Second - > 5x5x8 Third - > 5x5x16 and final ...
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How can the convolution operation be implemented as a matrix-vector multiplication?

How can the convolution operation used by CNNs be implemented as a matrix-vector multiplication? We often think of the convolution operation in CNNs as a kernel that slides across the input. However, ...
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How is the convolution operation used in CNNs a special case of the convolution operator?

How is the convolution operation used in convolutional neural networks (CNNs) a special case of the mathematical convolution operator? Most of us, when we think of the "convolution operation", we ...
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Siamese Network for unknown object

I am currently trying to create a One-Shot network using the Siamese architecture for an object that isn't a face. My problem is, in normal Face Recognition the detecting gadget (e.g. Smartphone) ...
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Count number of objects in image using CNN

I'm looking for neural network architecture that excel in counting objects. For example, CNN that can output the number of balls (or any other object) in a given image. I already found articles about ...