Questions tagged [convolutional-neural-networks]

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

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10
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5answers
6k views

What is the fundamental difference between CNN and RNN?

What is the fundamental difference between convolutional neural networks and recurrent neural networks? Where are they applied?
2
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0answers
352 views

Similarity of images (CBIR) with CNN features

I am trying to build a neural network suitable to measure similarity between pairs of images. In particular I am interested in shoes. I have a query image (e.g. a shoe that I just took a picture of) ...
2
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1answer
2k views

What fast loss convergence indicates on a CNN?

I'm training two CNNs (AlexNet e GoogLeNet) in two differents DL libraries (Caffe e Tensorflow). The networks was implemented by dev teams of each libraries (here and here) I reduced the original ...
2
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1answer
417 views

What is the meaning of a 2D stride?

I know what meaning stride has when it is just an integer number (by which step you should apply a filter to the image). But about (1, 1) or even more dimensional ...
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1answer
115 views

Can CNN autoencoders be improved by treating the output layer as an inverted hidden layer?

I wish to write a bot that can use screen footage to play a game, specifically for the game 'Nidhogg'. To that end I have determined that a CNN should do the feature detection and a feedforward ...
3
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3answers
334 views

Would convolutional NN recognize patterns in encoded images?

I have a set of images that I already trained a CNN to classify successfully. I wonder if it would be possible to encode the images (using XOR in combination with a key of the same length as the image)...
5
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2answers
2k views

Can Convolutional Neural Networks be applied in domains other than image recognition?

I'm new in this argument, my question is: Can convolution be applied in other contexts different from image recognition? Is there a good source to learn from?
14
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0answers
2k views

What's the main concept behind capsule networks? [duplicate]

As you might know, capsule networks have been recently introduced by Hinton. There also have been several heads up within his talks. As expected, the paper elaborates on the idea way theoretically! ...
2
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1answer
426 views

Constraining the output value range of a CNN independent of the loss function

I'm having the following problem: ` I'm training a multi-output CNN and using the relative values of the outputs in my loss function. The net is learning well, but as the absolute values of the ...
6
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4answers
2k views

Why my test error is lower then train error

I am trying to train a CNN regression model using the ADAM optimizer, dropout and weight decay. My test accuracy is better than training accuracy. But as I know, usually train accuracy is better than ...
2
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1answer
756 views

What are the counterparts of non-linearities and dropout in fully convolutional networks?

I am trying to replicate the fully convolutional networks (FCN) concept described here for semantic segmentation. It seems people have successfully trained such models by removing fully connected ...
4
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1answer
2k views

How to train for own dataset really really fast while debugging

How to train darkflow for my custom object really really fast during debugging in quad core PC and without GPU? (Can I train with about 10 images and test with only those images, just to check if all ...
3
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3answers
105 views

Method for Multi-class/category?

I am having issues getting started with a multi class problem with multiple features and hoping someone could please point me in the right direction. I have data that is structured like this for ...
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0answers
59 views

Can Image Recognition used to find height of a person whole, torso, legs etc

Image recognition can be used to classify images. But I wanted to find few parameters like height of person, his legs, his hand etc. Will CNN helpful for this type of output ?
2
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0answers
47 views

Recommendations on which architecture to use to guess appointment

I'm currently developping an application which allows psychologists to manage their schedule and budget. As a proof of concept, I would like to create an intelligent appointment service. There can be ...
5
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1answer
530 views

What makes learned feature detectors specialize in CNN?

It has been shown that it is possible to use unsupervised learning techniques to produce good feature detectors in CNNs. I can't understand what drives specialization of those feature detectors. In ...
2
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0answers
203 views

Can anybody explain such behavior of accuracy and loss of my Net(caffe)?

I used this project for example(framework - caffe, arhitecture of net - mod of AlexNet, 400 images are used for training). I have this result: or this: Solver: ...
3
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1answer
1k views

How to detect the empty parking spots?

I have some images of the empty parking as shown below. I 'd like to use deep learning to extract the parking spots. But in the beginning,am confused whether there are several ways to do the ...
3
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1answer
204 views

ReLu, Sum and Convolution Layers to Count Pixels of Certain Color

Below is an excerpt in an instructor's manual on ML that is explaining deep neural networks, using cat recognition (what else!) from images as example. On how DL performs this feat, the excerpt said ...
4
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0answers
148 views

Game AI - Modify image classification model for analog output

I'm developing a Game AI which tries to master racing simulation. I already trained a CNN (alexnet) on ingame footage of me playing the game and the pressed keys as the target. I had two main issues ...
5
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1answer
411 views

Game AI - Fast python OCR or cropped image input

I'm developing a Game AI which tries to master racing simulations. I already trained a CNN (alexnet) on ingame footage of me playing the game and the pressed keys as the target. As the CNN is only ...
0
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1answer
4k views

Book recommendations on deep learning (convolutional neural networks) [closed]

I am working on software which deblurs the motion blur created by camera movement. I've surveyed some research papers and determined this process requires deep learning and CNN. Now I'm looking for ...
4
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1answer
763 views

Training Custom object detection network using tensor-flow object detection API?

I was just wondering if some one could provide a nice tutorial on how to use the Recent tensor-flow object detection API to train custom network say like VGG-16? (Just USE the VGG-16, VGG-19, ...
3
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2answers
174 views

Will CNNs kill CAPTCHAs or can they survive in an evolved form?

CAPTCHAs, which are often seen in web applications, are working under the assumption, that they pose a challenge which a human can solve easily while a machine will most likely fail. Prominent ...
3
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1answer
596 views

Intuitively understanding translational invariance in CNNs

I'm currently in the process of learning about using CNNs in image recognition. Many of the different resources I read that were explaining the motivation referred to the fact that these networks are (...
16
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3answers
28k views

How do I handle large images when training a CNN?

Suppose that I have 10K images of sizes $2400 \times 2400$ to train a CNN. How do I handle such large image sizes without downsampling? Here are a few more specific questions. Are there any ...
4
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3answers
164 views

Would this relatively small dataset be enough to train a CNN?

Scenario: I am trying to create a dataset with images of choice for different animal classes. I am going to train those images for classification using CNN. Problem: Let's assume I somehow don't have ...
6
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2answers
108 views

CNNs: What happens from one neuron volume to the next?

I've gone through several descriptions of CNNs online and they all leave out a crucial part as if it were trivial. A "volume" of neurons consists of several parallel layers ("feature maps"), each the ...
2
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0answers
371 views

CNN attention maps on non-images

My datasets are not actual images, so using methods with ImageDataGenerator or pre-trained networks might not apply in this case. Data Structure: Each "image" is a 2048-long vector that has float ...
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3answers
790 views

Ensemble Learning using Convolutional Neural Networks

I have created 22 different Convolutional neural networks that all test for the presence of unique objects in an image (each one of the classifiers is unique). Each sample in the test set has the ...
0
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2answers
258 views

Feature extraction other than convolutions for images?

Are there approaches other than convolutions to learn features from images? Has there been any research to use approaches such as hashing (e.g. p-hash, ...
4
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0answers
157 views

How to feed a variable size sequences into a CNN?

If I want to train a convoluted NN on time series but I cannot decide where to split the data. I see that other people use jumping window over the input. so the feed say 20 sec of observation as 1 ...
2
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1answer
835 views

How can I use a trained CNN to predict a new image label?

I was applying this CNN fine-tuning example from Matlab. The example shows how to fine-tune a pre-trained CNN on letters to classify images of digits. Now I would like to use this new fine-tuned CNN ...
8
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2answers
5k views

How do we choose the kernel size depending on the problem?

Obviously, finding suitable hyper-parameters for a neural network is a complex task and problem or domain-specific. However, there should be at least some "rules" that hold most times for the size of ...
3
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3answers
10k views

How to “combine” two images for CNN input (classification task)?

For a classification task (I'm showing a pair of exactly two images to a CNN that should answer with 0 -> fake pair or 1 -> real pair) I am struggling to figure out how to design the input. At the ...
3
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2answers
4k views

How is the depth of a CNN layer determined?

I am looking at a diagram of ZFNet in an attempt to understand how CNNs are designed effectively. I'm working with the CIFAR10 set in pytorch. In the first layer, I understand the depth of 3 (...
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2answers
2k views

Create your own CNN in java or c#? [closed]

I would love to learn how to create my own neural network from scratch so i can understand them better. My goal it's not so much to use their perception capabilities (classifying pictures) as it is to ...
0
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1answer
135 views

How to deal with changing video frame sizes in a CNN?

How to deal with videos where the frame sizes are not the same frame to frame? For example this video moves up and down and when it does, the video part of the screen has a different amount of pixels ...
2
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1answer
160 views

Training a convolutional network to recognize object location

I am beginning an image analysis project to recognize images with a particular object centered on the image. If the object is at the center, I give the image a positive label, and if it is anywhere ...
2
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0answers
541 views

3D - CNN. Why my cost function decreases, but the accuracy does not increase?

I'm implementing a C3D-inspired neural network for human emotion recognition, the problem I'm facing is that altough the cost function is decreasing, for both training and validation sets, I do not ...
11
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2answers
11k views

What are bottleneck features?

In the blog post Building powerful image classification models using very little data, bottleneck features are mentioned. What are the bottleneck features? Do they change with the architecture that is ...
1
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1answer
3k views

Neural network algorythms without any libraries [closed]

I am a php developer learning python for one reason, i wanna learn ai and i think that python would be better than php at that. I tried finding tutorials on how to build a neural network but they all ...
2
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4answers
408 views

Training neural network for good taste in art

I'm a newbie in machine learning, so excuse me in advance). I have an idea to make NN that can estimate visual pleasantness of arbitrary image. Like you have a bunch of images that you like, you train ...
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2answers
8k views

Concatenate convolution layers with different strides in tensorflow.

I am trying to do an inception layer, but it only works if the convolution strides, pool strides and pool size are the same, otherwise I get an error in tf.concat that Dimesion 1 is not the same. ...
1
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0answers
61 views

Can a CNN or MLP discover similar but untrained-on patterns?

I've been experimenting with a simple tic-tac-toe game to learn neural network programming (MLP and CNNs) with good results. I train the networks on a board positions and the best moves and the ...
5
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1answer
183 views

Can a purely policy convolution neural network based game learn to play better than its opponents?

This question has come from my experiment of building a cnn based tic-tac-toe game that I'm using as a beginner machine learning project. The game works purely on policy networks, more specifically - ...
9
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1answer
347 views

How much of a problem is white noise for the real-world usage of a DNN?

I read that deep neural networks can be relatively easily fooled (link) to give high confidence in recognition of synthetic/artificial images that are completely (or at least mostly) out of the ...
4
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1answer
695 views

How does visual cortex share convolution weight

TL;DR If we buy into the idea visual cortex functions like a convolutional neural network, then there's a problem makes me scratch my head: how does brain force weight sharing as in convolutional ...
5
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1answer
120 views

Use ConvNet to predict bitmap

I want to build a classifier which takes an aerial image and outputs a bitmap. The bitmap is supposed to be 1 at every pixel where the aerial image has water. For this process I want to use a ConvNet ...
5
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2answers
338 views

Feasibility of generating large images with a convnet

I've spent the past couple of months learning about neural networks, and am thinking of projects that would be fun to work on to cement my understanding of this tech. One thing that came to mind last ...