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Questions tagged [image-processing]

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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What would be the convolutional layer output by keras.layers.Conv2D when conv output is fractional?

I have input ($n=224$), strides ($s=4$), filter size ($k=11$) and no padding which gives me a fractional conv output: $$\texttt{conv output} = (n-k+2p)/s + 1 = 54....
Shri's user avatar
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Uncertainties when fitting an image

I know how to fit a straight line to a set of 2d points with uncertainties on both coordinates, in order to obtain estimators, goodness-of-fit, and uncertainties - see for instance Press & ...
Mister Mak's user avatar
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How to obtain the similarity ratio between graphs hand-drawn on paper?

To explain with an example: In one class, I showed students a plot that I wanted them to draw. They saw it as too short and tried to draw the same. Some were very similar, some were less similar, and ...
doqukan's user avatar
11 votes
1 answer
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Getting 99-100% accuracy on my training/validation data but performs bad on completely new data

I have a large dataset of the ASL (American Sign Language). I split this data into 70:15:15 for train, validation, test. I then trained a CNN model on it, where I trained using the 70%, and evaluated ...
codinator's user avatar
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How can you determine whether a feature vector extracted from an image is representative for a specific task?

In the task of scoring video frames based on their features for video summarization project, if the frame features are extracted using pretrained CNNs such as GoogleNet, VGG, and ResNet, how can I ...
moha tech's user avatar
1 vote
0 answers
33 views

Is it reasonable to use background subtraction to identify some objects in sequential frame images to start labeling objects for YOLO training?

I know background subtraction is not a complete solution for object detection, but I’ve tried it for identifying potential new objects appearing in fixed background camera scenarios (millions of ...
NominalSystems's user avatar
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10 views

Creating a light image generation model for a specific distribution

I am currently working on how a user can introduce bias in a neural network model. To do so, I am creating an image2image model that only works on the training distribution. For example, let's say I ...
Adrien's user avatar
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1 vote
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Impact of Pixel Normalization Technique on Weights, Gradients, and Activations in Neural Network

There are different ways to process an image either before or during the training of a neural network trained to take in image inputs. Some of the pixel adjustment techniques used: Scaling each pixel ...
Kinshu's user avatar
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Sensible neural network architecture for image stitching?

I am currently trying to design a neural network for image stitching, but I am having trouble coming up with a neural network architecture that seems suitable for the job. The input to my neural ...
Tue's user avatar
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Detecting Object Removal in Images

The problem statement is as follows - Given an altered image (an image from which some object has been removed), generate a mask for the removed object. For instance, say an original image contains ...
Aditya Kulkarni's user avatar
1 vote
0 answers
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Finding the most-similar color palette [closed]

I have a dataset of several thousand color palettes: for each row in a dataset, I have the ten most common RGB values in an image, and the fraction of that color in the overall image: ...
Saul Aryeh Kohn's user avatar
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1 answer
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K means clustering of image with k=1 vs mean of all pixels

I have relatively uniformly colored images and I extracted colors using k-means. k means 1 showed the best results for my modeling purposes, k means 2 not so much, and with k-means 3 there ceased to ...
phil27's user avatar
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Computer vision tool to match regions in two images at different pixel locations

I have two image files. One image has subplots of (100) stock price graphs with stock ticker labels. The other image has subplots of (112) stock price graphs shuffled to a different row and column in ...
Jose_Peeterson's user avatar
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0 answers
15 views

Increasing the clarity in the tasks of image generation using CNN

What methods exist to improve the quality of generated images and the clarity of contours in the tasks of image denoising/debluring (using CNN), style transfer etc? I am interested in approaches that ...
Alimagadov K.'s user avatar
2 votes
0 answers
127 views

Seeking Guidance on Constrained Input Modeling for Soil Moisture Correction Using Rainfall Observations

I find myself immersed in the intricacies of working with 2D modeled fields (images) representing soil moisture in regions where direct observations are unfortunately absent. However, there is a ...
Seyed Omid Nabavi's user avatar
1 vote
0 answers
39 views

Image Blur - Disc Kernel [closed]

I'm trying to use the blur() function from the spatstat package in R to blur an image. One ...
BurlyPotatoMan's user avatar
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0 answers
26 views

Query regarding MI and NMI in the context of image fusion

I am exploring Mutual Information (MI) and Normalized Mutual Information (NMI) in the context of image fusion. While reviewing various sources, it's often mentioned that Mutual Information's value ...
925678's user avatar
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Partial Differential Equations for Image Inpainting - Gradients and Orthogonal to gradients

I hope this is the correct channel. Following the Coursera course on image inpainting using PDEs [1], the instructor presents a method for image Inpainting that follows the next equation: $\frac{\...
mgbacher's user avatar
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16 views

Computing coordinates of points of an image after elastic deformation

My task is: given an image and set of points of interest, elastically and randomly deform the image and save it with the modified aforementioned points. example: (blue points are the points of ...
FirePapaya's user avatar
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0 answers
17 views

Remove non repeatable stochastic noise from an image

Assume that you have these coordinates inside an image. The algorithm for creating these crosses comes from FAST-algorithm for corner detection. But the problem with FAST-algorithm is that some of ...
euraad's user avatar
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Fully Convolutional Networks: Fully Connected Layers as Convolutional Layers

I'm reading the paper "The Fully Convolutional Network" and I don't understand this passage in 3.1: Typical recognition nets, including LeNet [21], AlexNet [19], and its deeper successors [...
user0906's user avatar
1 vote
0 answers
22 views

A method to categorize variations in time series of images

I am working with a time series of remote sensing images from a particular area. Temporal standard deviation (SD) of these images showed high fluctuations at some regions with SD of 1.17 while some ...
sat_P's user avatar
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0 answers
47 views

Formula/Proof: How many times must maxpooling (3x3 kernel, stride 2x2) be applied for a random binary mask (dxd size) to have only 1 values?

Given a d x d array, 1% of which contains the value 1 and all remaining locations contain the value 0. (e.g. a 128 x 128 array would have 164 values equal to 1 and 16220 values equal to 0). What would ...
Yatagarasu50469's user avatar
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0 answers
19 views

Training problem in CNN model for image classification

I am training Cifar-10 dataset of 32 x 32 sized coloured images for image classification. Here is the link/source to the dataset and its description: https://www.cs.toronto.edu/~kriz/cifar.html The ...
keen_Learner 's user avatar
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0 answers
36 views

Image processing: Inferre rotation angle of tilted rectangle on noisy background

I have many "grayscale" images i.e. 2d-arrays like the following: i.e. dark rectangles which are tilted by an angle $\alpha \in [-3^\circ, 3^\circ]$ and a bright but noisy background. I ...
cknoll's user avatar
  • 133
3 votes
1 answer
219 views

Can translation invariance be achieved by just a global pooling layer?

I am trying to understand the purpose of the max pooling layers that are insterted between intermediate convolutional layers. As we know, the outputs of convolutional layers are translational ...
ado sar's user avatar
  • 477
2 votes
2 answers
494 views

Entropy of an Image?

In a previous question (Entropy of an image) and in various sources on the web, the Shannon entropy of an image is considered to be the entropy of the frequency distribution of the grayscale values. ...
Edoardo's user avatar
  • 21
1 vote
0 answers
52 views

What is the best strategy to determine the final weights of the model after doing k-fold cross-validation?

Suppose we are building a CNN model. After we do 5-fold cross-validation and examine the accuracies and other statistical tests, how do we choose the final weights of the model? Should we choose the ...
Ola Galal's user avatar
-1 votes
1 answer
79 views

Machine learning and Artificial intelligence algorithms in identifying and classifying Airplane parts

Airplane parts and functions Can Machine Learning and Artificial intelligence Algorithms assist in identifying and classifying Airplane images parts?
Prashant Akerkar's user avatar
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0 answers
21 views

PCA components - do they represent the features or the samples?

Consider the task to apply dimensional reduction to extract "salient" features from images. I am confused about what components in PCA represents: features or samples ? I understand that PCA ...
user305883's user avatar
1 vote
0 answers
27 views

How to measure effective sample size for multivariate time series?

I am working with images collected over time from a fixed camera. Since the scene doesn't change for long periods, my effective sample size is much lower than the actual number of images I've ...
ted's user avatar
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0 answers
28 views

What is a feature of an image?

Given an image to train on a CNN what would be considered the features that are the inputs of the model? Would each individual pixel be a feature or would the R,G,B channels be the features? Lets say ...
Hayden LaBrie's user avatar
5 votes
0 answers
45 views

Fused lasso for image denonising

For a given data $y_{i}$, with $i=1, \dots, n$, we consider the following signal approximation: $$ \hat{y} = \arg \min_{w}\sum_{i=1}^{n}(y_{i}-w_{i})^{2} + \lambda \sum_{(i,j)\in E}|w_{i} - w_{j}|, $$ ...
ABK's user avatar
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4 votes
2 answers
114 views

What are the best resources on image synthesis?

What are some good resources to learn about image synthesis? What are some of the key concepts or architectures to study? I understand image synthesis as generating new images with ML techniques.
Glue's user avatar
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0 votes
2 answers
75 views

Model giving accuracy of 89% after training it by CT scan Images. and giving accuracy of 35% on testing. and low precision, recall, f1-score [closed]

I am training a model for cancer detection by using chest CT scan Image. training set is 70% testing set is 20% validation set is 10%. Data contain 3 chest cancer types which are Adenocarcinoma, Large ...
Praveen Rawat's user avatar
0 votes
0 answers
32 views

Looking for a goodness-of-fit measure for fitting a model to an image

I am trying to fit a model to a noisy image. After fitting, I would like to have some way of assessing the quality of the fit (i.e. whether there are any systematic deviations of the model from the ...
Ewout's user avatar
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6 votes
1 answer
2k views

How to determine if two images contain the same object without a dataset?

The problem I am trying to solve is, given two images, determining whether they contain the same object or not. Here is an example: The first two images contain the same object, while the third image ...
NoahGav's user avatar
  • 161
4 votes
3 answers
206 views

Should a CNN generalize to arbitrary positions in the data?

I have trained a CNN on one dimensional data that is the power spectral density (PSD) of a $N$ different classes of signals ($N=4$). Each of the $N$ signals has a different spectral shape (not shown ...
BigBrownBear00's user avatar
0 votes
0 answers
92 views

Standard Deviation of Averaging filter

I am wondering why the standard deviation of the averaging filter of width w is as follows? Where does the 12 in the denominator come from? For context, the paper is am refererring to can be found ...
Ash's user avatar
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1 vote
0 answers
207 views

Regression summary returning coefficients with value and standard error equal to zero

I'm creating a classifier using linear regression to classify images of hand-drawn digits from the MNIST dataset. I realize that linear regression is not the appropriate approach, but this is for a ...
jmoore00's user avatar
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0 votes
0 answers
62 views

When to use Padding when Randomly Cropping Images in Deep Learning?

I am seeing these two options to process mini-imagenet images during training: Option 1 torchmeta: ...
Charlie Parker's user avatar
0 votes
0 answers
31 views

Evaluation metrics of XAI techniques output

Consider multiple videos with N frames. I have M models and X XAI methods. Basically, i've trained and evaluated some models (classification task, real/deepfake) on these N frames and I've obtained ...
ccragusa's user avatar
0 votes
1 answer
118 views

What kind of architecture to use for non-binary output multi-label image clasification

I want to make a network for making multi-label attribute classifications on images of clothing. This is a simplified case of what I want to do, I have 9 different attribute categories that I wish to ...
isa türk's user avatar
  • 101
0 votes
2 answers
1k views

How to calculate the transalation and/or rotation of two images using fourier transaform?

I need find the translation and/or rotation of an image and himself translated and/or rotated (x0, y0) px and/or J degrees. Given the two images I need to find N.
Sebastian Jose's user avatar
4 votes
1 answer
608 views

Is there any well-founded way of calculating the euclidean distance between two images?

I need to determine the distance between two images. Supposing that we are dealing with images of the same size, I think that we can reduce this problem to the square root of the sum of the square of ...
Zaratruta's user avatar
  • 1,018
1 vote
1 answer
70 views

Standard deviation of symmetric data

Within my field a recent study suggested to use the symmetric properties of certain image datasets to improve signal to noise ratio (SNR). I will spare you the details, but in the end one can get a ...
user avatar
1 vote
1 answer
1k views

Best reconstruction loss for RGB images?

Which loss works the best for pixel-wise RGB image (3, width, height)reconstruction loss? It seems there are several options Regression way. The input image has ...
MerelyLearning's user avatar
1 vote
0 answers
211 views

How to explain the high accuracy and F1 score on the test set with a huge binary crossentropy loss?

I'll provide a little of introduction based on my example. I have a small collection of RGB (but 'gray-looking') brain MRI photos, divided into 2 classes: healthy and tumor. My data split looks like ...
Karolina Świergała's user avatar
0 votes
0 answers
29 views

Pix2Pix facede dataset, prevent "gray" in dataset to be predicted

I'm trying to build from scratch the pix2pix architecture, the one on this paper. As they did, I'm using the facade dataset, and this is one of their result: I'm particularly interested in the last ...
Alberto's user avatar
  • 1,217
3 votes
1 answer
350 views

Centering in normalized cross correlation for template matching

Context I'm following Lewis (1995) exposition on normalized cross correlation for template matching (Section 2). The cross-correlation of the image and the feature at $u,v$ is denoted by $c(u,v)$ and ...
Simón Ramírez Amaya's user avatar

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