A form of signal processing where the input is an image. Usually treating the digital image as a two-dimensional signal (or multidimensional). This processing may include image restoration and enhancement (in particular, pattern recognition and projection).

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How to think about the architecture of the Convolutional Neural Network?

Recently, I've started to learn more about CNNs to use them in some computer vision tasks. At the moment, I have roughly good knowledge about different parts of a CNN such as layers, solvers, loss ...
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18 views

What is zero mean and unit variance in terms of image data?

I am new to deep learning. I am trying to understand some concepts. I know "mean" is an average value and "variance" is deviation from mean.I have read some research papers, all say that we ...
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1answer
18 views

Convolutional Neural Network for 3D point cloud?

Can Convolutional Neural Networks or Deep Architectures be used for generating 3D point clouds ?
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8 views

Is there any software package to minimize the weighted total variation for image recovery? [closed]

I would like to recover my original image using the following weighted total variation minimization. I have the implemented package for unweighted but i have no idea how to solve this one using ...
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10 views

Neural Networks in Image Processing - Literature Reviews

I'm looking for good Literature Reviews on the use of Neural Networks in "Image Processing/Image Retrieval/Image Classification" and generally anything Image Related... Has some work been done in ...
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7 views

Detecting images inside website snapshots and extracting them with machine learning

I was wondering if I could detect images inside website snapshots and cut them out of the snapshot. for example I can download Image Snapshots from any website via PhantomJS. this gives me a ...
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31 views

Help in understanding a clustering technique using neural network

I am having difficulty in understanding a technique for clustering and segmentation of biomedical images using the concept of time series. The paper on which the Question is based is : M. Lacomi et. ...
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32 views

What is the efficient preprocessing data in image classification task with CNN?

I am new in deep learning on image classification. I know that Machine learning algorithm are very dependent to data normalization. Usually, if we have a training data set represented with X [N*D] ...
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1answer
48 views

Translational variance in convolutional neural networks

Convolutional networks have been proven to work very well detecting a shape independently of where it is in the image, which is referred as translational invariance. In the case where the position ...
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1answer
20 views

What advices do you have for a starter in multiple image recognition?

So, I have experience in machine learning for NLP and a little in neural networks for NLP, but never so far done anything in computer vision in this area so bear with me if what I am asking is a ...
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16 views

Help in understanding an image clustering technique described in a paper

Paper titled :Mammographic images segmentation based on chaotic map clustering algorithm DOwnload link presents a technique of image clustering using chaotic map. I explain briefly : A chaotic map is ...
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27 views

No change in accuracy big vs small training set size ConvNet

I am doing some small experiments with image classification in Caffe using the AlexNet architecture. I use a dataset of 50 classes with each class containing 1,000 training images. After about 2k ...
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1answer
21 views

Drop in results upon addition of new features in random forest model

I am training a classification random forest for object detection in images. I have several features (like HoG, edge features etc) which work good enough separately. But when I train using all ...
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13 views

Understanding filter space in convolutional neural networks and its reduction in Inception architecture

From this source I acquired a quite good understanding of 1x1 convolutions in Inception CNN and how they perform a reduction in the filters dimension. There is one thing I would like to clarify ...
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18 views

How to use a neural network in image recognition? [duplicate]

I understand the idea behind neural networks, but i do not comprehend the practical application of one in an image. For example, if I train a network against a photo of the letter 'A' (30 x 30 ...
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41 views

Image Segmentation with a challenging background

[cross-posted from datascience, as no answers received] I'm working on an animal classification problem, with the data extracted from a video feed. The recording was made in a pen, so the problem is ...
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0answers
31 views

Face authentication system using Convolution Neural Network (CNN)

I'm working on developing an face authentication system using Convolution Neural Network (CNN). I know that the CNN can be used to classify two classes. However, my problem is how can I train the CNN ...
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1answer
90 views

How to train convolutional neural networks with multi-channel images?

I have $m$ labeled images, each with 224x224 pixels and 5 different image channels. What is the best way to train a CNN architecture using this data when $m$ is small (less than 2000)? Is it possible ...
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1answer
48 views

Question about prior in bayesian image processing

I am learning Bayesian image processing. Bayesian approach will take prior knowledge about image into account. From one material, it says knowledge is expressed via probability functions. I understand ...
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1answer
119 views

Class Balancing in Deep Neural Network

I was trying to do class balancing on the image semantic segmentation problem for some classes in the images are in the minority. The weight for each class is calculated as mentioned in this paper: ...
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3answers
59 views

Add New Object Class in Deep Learning Network

Assuming that I have a trained deep learning network that can detect 10 classes of objects (road, sky, tree, etc.) in images. It takes in RGB images and outputs a probability map of size ...
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20 views

Ising-Like Priors with Fractal Boundaries (Application to Image Processing)

Overview: I'm interested in looking for priors that "look a little like" the Ising model, but have different large-scale behaviour. In particular, I'm looking for priors that give rise to large ...
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0answers
40 views

Improving the results coming from an image recognition API

We are developing a software application that will automatically suggest tags (keywords) for images that are being uploaded into a database of already-tagged (by a human) images. We are using a 3rd ...
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2answers
42 views

What it mean by Training SVM

I am new to image processing. As my project I am doing "image classifier using SVM". I have the idea of my final software "I select some image and give it as input to my software and it will classify ...
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49 views

Looking for a CNN implementation for 3D images

I'm looking for an implementation in python (or eventually matlab) of Convolutional Neural Networks for 3D images. By 3D I mean 3 spatial dimensions (i.e. not 2D+channels or 2D+time). Any advice?
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26 views

Time series and images : difference and terminology

A time series is an ordered collection of random variables. Considering a one-dimensional time series $A_i = {a_{i1},a_{i2},\ldots,a_{it}}$ where $t$ denotes the time index. So, the time series is a ...
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1answer
38 views

Need guidance on image classification problem with large feature matrix

So I've got an interesting problem that I'm struggling with and I wanted to hear some ideas on possible solutions. The data is not public and I can't go into much detail. The problem involves a ...
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27 views

Detect bounding box of tables in PDF page

I am new to Machine Learning, doing courses and reading papers, and would like to solve the following problem as my learning journey: Given a PDF page I would like to detect the bounding boxes of all ...
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70 views

find outlier in 1D array

I have a satellite images, which have none values (which are not all equal to 0) on right and left side of an image and it is not a strait line. I would liked to write a program, which finds the ...
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0answers
20 views

CNN localizing object?

For classying images/objects CNNs are one possible or even the state-of-the-art solution but what if one wants to localize an object in an image? I thought if I use only convolutional layers without ...
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0answers
38 views

Help: Random Forest optimization (image classification)

I'm having trouble classifying images using a random forest. The images all have a very similar scale, but they may be rotated arbitrarily around a fixed point in the image. The core problem is ...
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0answers
14 views

how can use otsu's method?

I want to do binarization on my images. if my images have Intensity homogeneities, it means that they don't have local variation in both background and foreground I can use global thresholding. I ...
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0answers
63 views

Image recognition fails when given image not in training set

I am a beginner in Neural network. What I am trying to implement is an image recognizing tool. Neuroph Studio was used for training and creating the trained data set. A set of images of cars were ...
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0answers
23 views

Shifting input over image for CNN object detection?

I've got a CNN which is trained supervised and calculates if a specific object is present in an image. Since I am interested in the object's position in the image I tried to alter my architecture so ...
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1answer
61 views

How to prepare colored images for neural networks?

I have seen many examples online regarding the MNIST dataset, but it's all in black and white. In that case, a 2D array can be constructed where the values at each array element represent the ...
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0answers
80 views

Neural Network for Image Recognition fails to converge

I have implemented a MLP neural network, which is being used to recognise human faces. The NN's input layer has 175 neurons which represent an image (25x25 dimensions), the data for each image is ...
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1answer
41 views

Recognition of digit of size other than those in the training set using DNNs

I have a DNN trained on MNIST data (image 1 for digit '4') that recognizes images from the test set with high precision. Each digit is centered and all of them are roughly of the equal size. Will it ...
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2answers
82 views

Theoretical justification for bag of words

Bag of words and visual bag of words are successful machine learning approaches. Does anyone know of a theoretical justification for why / when they work? What I am trying to explain is the good ...
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0answers
10 views

What are state-of-the art scanned page segmentation techniques?

I am interested in extracting images from scanned book pages. I assume this is something Google would do for their image search, since they have scanned millions of books. After a quick look at the ...
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1answer
110 views

Why do we need to normalize the images before we put them into CNN?

I am not clear the reason that we normalise the image for CNN by (image - mean_image)? Thanks!
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0answers
25 views

What are good / simple techniques available for segmenting non-cursive handwriting images?

I need to process English hand-written form fields. So the hand-writings are expected to be mostly non-cursive but the letters may occasionally overlap with each other slightly, with some punctuation ...
3
votes
1answer
564 views

Comparing two histograms using Chi-Square distance

I want to compare two images of faces. I calculated their LBP-histograms. So now I need to compare these two histograms and get something that will tell how much these histograms are equal (0 - 100%). ...
2
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0answers
248 views

Recurrent neural network for object tracking & position filtering?

Would a recurrent neural network be appropriate for object tracking tasks? Mainly I will have 3D feature vectors $(x, y, t)$ where $x$ and $y$ are the positions of an object in the image and $t$ is ...
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1answer
75 views

Advantage of latent SVM for part-based object detection

In the famous paper Object Detection with Discriminatively Trained Part Based Models, the authors use a Latent SVM approach to learn the detector of each part, because the localization of the parts in ...
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1answer
52 views

Sensitivity of DNN-based classifiers to centering and orientation of object in images

Is DNN classification senstitive to centering and orientation of object in images? for instance: Let us assume that a DNN is trained with letters always appearing in the same given orientation (e.g. ...
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0answers
26 views

Uncertainty in pixel intensity value due to the spatial uncertainty of phenomena

Assume we have image of point object (I use Gaussian PSF). Let's assume that position of this point object is not precisely known due to some phenomena. Spatial position of point source can be ...
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1answer
61 views

How do I compute a realization of h(x) given its PDF and covariance?

I've added a picture of what I want to compute. In the nomenclature of the picture, I want to compute a realization of y(x) given the known distributions and constants. Let's say y(x), random ...
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1answer
181 views

Feature detection from satellite images

I'm having a couple of thousand clear satellite pictures and would like to extract features out of them, like outdoor swimming pools, solar panels, presence of green space, ... I was wondering if ...
2
votes
2answers
102 views

Data augmentation step in Krizhevsky et al. paper

In the paper Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E. Hinton. "Imagenet classification with deep convolutional neural networks." Advances in neural information processing systems. 2012., ...
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53 views

CRF or MRF energy functions for image segmentation

I am currently working on image segmentation for the purposes of computer vision. I have read many papers and a few books dealing with MRFs and CRFs for computer vision. All of them define an energy ...