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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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7
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6answers
1k views

Why Python not C?

I like the enforced indentation of Python that many don't like because I hate parenthetic typing and redundant semicolons. I like the shell interface, but why do some think Python is de facto for ...
4
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1answer
325 views

Identifying car model via deep learing

Is there any project or example for a software identifying cars? Situation: I got multiple angle shots in high resolution from a car. I want the algorithm to tell me "This is a Mercedes SLK" or "This ...
1
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0answers
26 views

In CNN (Convolutional Neural Network), does the combination of previous layer's filters make next layer's filters?

I know that the first layer uses a low-level filter to see the edge information. As the layer gets deeper, it will represent high-level (abstract) information. Is it because the combinations of ...
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0answers
71 views

Using CNN LSTMs for prediction of images from image series

I have the following setup for a prediction task: I want to predict entire pictures from previously given pictures. In my case, only 2 pixels in every frame are neither black nor white, they are some ...
1
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0answers
64 views

How do GAN's generator actually work?

I have implemented DCGAN's myself and have been studying GAN's for over a month now. Now I am implementing the pggans but I encountered a sentence When we measure the distance between the ...
1
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1answer
555 views

How to label training data for YOLO

I am having a question on how to label training data for YOLO algorithm. Let's say that each label Y, we need to specify [Pc, bx, by, bh, bw], where Pc is the indicator for presence(1=present, 0=not ...
11
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3answers
936 views

What topologies are largely unexplored in machine learning?

Geometry and AI Matrices, cubes, layers, stacks, and hierarchies are what we could accurately call topologies. Consider topology in this context the higher level geometrical design of a learning ...
9
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4answers
598 views

Beyond neural networks?

Are there possible algorithms that have the potential to replace neural nets in the near future? And do we need that? What is the worst thing of using neural networks in terms of efficiency?
2
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1answer
53 views

Are there benchmarks for assessing the speed of the forward-pass of neural networks?

I have a task where I would like to use a convolutional neural network (CNN). I would like to incrementally start from the fastest models, fine-tune and see whether they fit my "budget". At the moment,...
3
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5answers
2k views

CNN with OpenCV

I have practiced building cnn for image classification with tensorflow, luckily to me they have very good library documentation and tutorials. But i found that tensorflow is too complicated, building ...
3
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1answer
543 views

Regarding Yolo and Keras

I'm trying to implement YOLO (tiny version, v1) into Keras framework. For the past two days, I've been relentlessly digging through Github and the likes in order to ...
2
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1answer
133 views

Neural network architecture for line orientation prediction

Imagine that a line divides an image in two regions which (slightly) differ in terms of texture and color. It is not a perfect, artificial line but rather a thin transition zone. I want to build a ...
2
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1answer
54 views

What are some resources regarding the complexity of training neural networks?

In the paper "Provable bounds for learning some deep representations", an autoencoder like a model is constructed with discrete weights and several results are proven using some random-graph theory, ...
0
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1answer
126 views

Using CNN to identify buildings from aerial images

I want to train a CNN (Vggnet) to identify different types of buildings from aerial images. However seeing that a CNN "ignores" size, e.g. the same type of dog in one image can be large and small in ...
7
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3answers
211 views

CNN's vs Densely Connected NN's

In image classification we are generally told the main reason of using CNN's is that densely connected NN's cannot handle so many parameters (10 ^ 6 for a 1000 * 1000 image). My question is, is there ...
4
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3answers
687 views

Convolutional neural nets and reduction of the layers

I have a very simple question about Conv nets. I understand the whole principle, but only one thing is not well explained on the Internet. If I have a 16 channels image that goes on a convolutional ...
4
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3answers
96 views

What kind of neural network architecture do I use to classify images into one hundred thousand classes?

I have an image dataset where objects may belong to one of the hundred thousand classes. I want to know what kind of neural network architecture should I use in order to achieve this.
3
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2answers
1k views

What is the purpose of “reshaping it into the shape the network expects and scaling it so that all values are in the [0, 1] interval.”?

I am a deep learning beginner recently reading this book "Deep learning with Python", the example explains the process of implementing a greyscale image classification using MNIST in keras, in the ...
2
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1answer
509 views

How to load an image into tensorflow.js code which reads handwritten numbers and clasify them

I'm new to machine learning, so i figured I should look into google's tensor flow guides and I know how to code in JS so that's why I'm using tensorflow.js, there's and example in the guide that ...
1
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2answers
1k views

Speeding up CNN training

So I built a CNN without any scientific libraries like TensorFlow or Keras (only NumPy). It is taking a huge amount of time to train. What are some of the tricks and tips followed by people to speed ...
1
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0answers
77 views

Object recognition by two or more traits that are orthogonal (informally speaking)

I would really appreciate if someone could comment the following method of training neural nets providing them with some meta data (Making them more color prone only if needed, whereas now they're ...
1
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3answers
81 views

Which photo is more artistic?

I would like to develop a machine learning algorithm, given two photos, that can decide which image is more "artistic". I am thinking about somehow combining two images, giving it to a CNN, and get ...
2
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2answers
189 views

How to make a fair comparison of a convolutional neural network (cNN) vs a mutlilayer perceptron (MLP)?

I'm working with deep learning on some EEG data for classification, and I was wondering if there's any systematic/mathematical way to define the architecture of the networks, in order to compare their ...
4
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1answer
73 views

Relative compute time for each type of layer in a neural network

Hello, I would like to know whether this picture from the paper: Distributed Training of Deep Neural Networks: Theoretical and Practical Limits of Parallel Scalability valid? Questions: 1) Does ...
3
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1answer
1k views

What is feature embedding in the context of Convolutional Neural Networks?

What are feature embeddings in the context of Convolutional Neural Networks? Is it related to bottleneck features or feature vectors?
1
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1answer
49 views

Detecting Keypoint of 3D model, and distance between them

I am very new to AI, I have a set of 3D human models that I would like to train the algorithm to identify wrist, upper arm, lower arms, etc, and distance between them. From my understanding, this is ...
3
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1answer
1k views

Detecting license plate using tensorflow

I'm currently working on license plate recognition. My system consist of 2 stage: (1) License Plate region extraction & (2) License Plate region recognition. I'm doing (1) with Raspberry pi 3 ...
2
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1answer
592 views

Custom Object Detection model including orientation of the Object

I am looking to detect think objects like pens, pencils and surgical instruments. The bounding box is not important, but I am looking to see if I can train a model to detect both the object as well as ...
5
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2answers
63 views

Can translational invariance of CNNs be unwanted if object is likely in certain positions?

Various texts on using CNNs for object detection in images talk about how their translation invariance is a good thing. Which makes sense for tasks where the object could be anywhere in the image. Let'...
1
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0answers
124 views

Normalizing height data for CNN

A task I’m working on at the moment requires a CNN with a height map as one of the inputs. This is a matrix of floating point values in which each point is the height of that point above sea level. I’...
4
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1answer
2k views

Why to prefer ReLU over Linear activation functions?

ReLU : y = max(0,x) Linear : y = x The ReLU nonlinearity just clips the values ...
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0answers
29 views

Atrous (Dilated) Convolution: How one can compute responses of arbitrarily high dimensions in DCNN?

According to this paper (page 4, bottom-right), atrous convolutions can be used to compute responses of arbitrarily large dimensions in Deep Convolutional Neural Networks. I do not understand how ...
1
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1answer
87 views

Is this overfitting avoidable?

I am trying a modification of Mobilenet in which I add feedback from the softmax layer into the early layers (to implement this I put a second net after the first, which receives connections from the ...
1
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1answer
135 views

Capsule Networks - Facial Expression Recognition

I want to experiment Capsule Networks on FER. For now I am using fer2013 Kaggle dataset. One thing that I didn't understand in Capsule Net was in the first conv layer, size was reduced to 20x20 - ...
8
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4answers
7k views

Convolutional neural networks with input images of different dimensions - Image segmentation

I'm facing the problem of having images of different dimensions as inputs in a segmentation task. Note that the images do not even have the same aspect ratio. One common approach that I found in ...
3
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2answers
307 views

VAE image reconstruction question?

Is it possible to use a VAE to reconstruct and image starting from an initial image instead of using K.random_normal as show in the “sampling” function of this example? I have used a sample image ...
3
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1answer
103 views

Neural Network training beginner question

I have a question about the training sequence regarding Neural Network recognition. Let's say an image has 28*28 pixels, which leads to 784 Input Nodes with various greyscale values and 10 output ...
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0answers
37 views

The relationship between CNN terms

I'm new to CNNs and am wondering if I understand the relationship between the following terms: In image analysis, receptive fields group "input neurons" to reduce the connection to the next layer. ...
2
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1answer
87 views

Video clip classification

My objective is simple...classify the given sequence of images(video) as either moving or staying still from the perspective of the person inside the car. Below is an example of the sequence of 12 ...
0
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1answer
836 views

Can YOLO detect large objects?

I have a rather basic question about YOLO for bounding box detection. My understanding is that it effectively associates each anchor box to a 8-dimension output. During testing, does YOLO take each ...
5
votes
1answer
87 views

How can neural networks that extract many features be fooled by adversarial images?

I have been reading a bit about networks where deep layers able to deal with a bunch of features (be it edges, colours, whatever). I am wondering: how can possibly a network based on this '...
1
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1answer
48 views

How to manage high numbers of input layer data points

Not sure if this is the correct forum, but I have been working with a large (non-image) dataset that will eventually be used to train a neural network. I have been puzzling over how to manage wide ...
3
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0answers
498 views

How to calculate gradient of filter in convolution network

I have similar architecture like in image:CNN. I don't understand how to calculate gradient of filter F. I found these equations(source): Gradient and delta, where first equation calculate gradient ...
0
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1answer
537 views

understanding strides and movement

I'm currently reading this explanation of convolutional neural networks and there's a part around strides that I don't quite understand. I'm just starting with this so apologies if this is a really ...
2
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1answer
663 views

3D convolution Neural Nets

I am trying to do 3d image deconvolution using convolution neural network. But I cannot find many famous 3d convnets. Can any one point out some for me? Background: I am using PyTorch, but any ...
1
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0answers
113 views

Questions regarding keras activation maximization visualization

I wanted to use the visualization of the activation maximization of the filters that is described in the following keras tutorial/blog: https://blog.keras.io/how-convolutional-neural-networks-see-the-...
1
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0answers
30 views

FIlling space with empty bounding box

I'm detecting objects on images. I want to detect up to 10 objects, however, I'm not sure how to deal with the situation, where only one object is present. Should I fill the remaining spaces in the ...
1
vote
1answer
83 views

Extracting one class from a pretrained Convolutional Neural Network

I am new to deep learning and computer vision. I have a problem where i use yolo algorithm (https://pjreddie.com/) to detect objects. In the original paper, they define the output to recognize 80 ...
4
votes
1answer
676 views

How well can CNN for bounding box detection generalise?

Suppose a CNN is trained to detect bounding box of a certain type of object (people/cars/houses/etc.) If each image in the training set contains just one object (and its corresponding bounding box,) ...
3
votes
3answers
105 views

Good idea to assign different objects to same class?

Suppose one trains a CNN to determine if something was either a cat/dog or neither (2 classes), would it be a good idea to assign all cats and dogs to one class and everything else to another? Or ...