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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Handling different image sizes in a VAE

I am working on segmentation and classification of cells based on their shape. After segmentation using CNN my images have different sizes. Next I want to run these images through a VAE for ...
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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 ...
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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 ...
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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 ...
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How to measure auto-correlation of pixels in a video?

I am working with climate variables time series (such as temperature, wind speed and humidity) and would like to understand how the wind speed (e.g.) at a place is influenced by other entries, by ...
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Throwing up error on reconstruction of image data while training VQ-VAE

I have been working on the VQVAE model implementation based on the code(and formatting data) according to this link. This resulted in that I was able to run the model successfully and get the .pth ...
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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 ...
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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 ...
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Data standardization for thermal images

I want to create a object classifier and instance segmentor. The data are thermal images, the temperature information is encoded using some pseudo colour palettes, and they can vary, depending on the ...
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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: ...
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Chi square for comparing image and models

In this question, the data is a 2D array which represents an image. Each element in the array is the flux or brightness of a given pixel. As a second step, portions of the image are masked (pixel ...
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Feature extraction using VGG 16

I was wondering if I could get an answer to something. I want to do feature extraction using pre-trained VGG 16. We know it's trained on 224X224X3 size images. So I ...
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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 ...
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Inverse Reinforcement learning on historical data in the form of images

I have historical data in the form of images/video frames and an action space. I am working on building an inverse reinforcement learning approach where the model can take previous expert ...
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How to filter or otherwise remove periodic noise from an image?

We are taking mostly-empty images of a system with a slow, low-noise CCD. Many of our images look like the following, where the object of interest is the bright streak, while a clear repeating pattern ...
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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 ...
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Cycle detection on unsupervised time series data

i have some video data of production lines of some manufactories. In every video, an operator does the same 3-4 steps periodically for the entire video. Each periods of same steps is called cycle and ...
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Tagging images with MLP based on embeddings - dynamic output

I have implemented a network consisting of: autoencoder - whose task is to reconstruct the images to then obtain an embedding vector for each image MultiMLP - whose task is to propose tags for a ...
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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.
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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 ...
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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 ...
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Computing the correlation index when there are few values available

I'm investigating the effect of image quality on system performance. That is, I have an image processing pipeline that receives an image as an input and delivers a function. Now I wanna statistically ...
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1 vote
1 answer
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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 ...
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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 ...
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Image preprocessing guidance for a Multi-class image classification problem

Scenario Multi-class image classification of mechanical parts. The Train set contains images of parts on a white background. The Test set contains images of parts from the workshop. Parts are ...
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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 ...
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Better noise distribution in GANs?

I am just wondering if there is something analogous to the Kaiming He Initialization in GANs for better training (better convergence, training time, etc.)? For example, can the generative model use ...
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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 ...
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Predict the missing pixel value by CNN

The data is images which resize to 256*256. And for per 8x8 area, we remove 4 pixels from the 8x8 block. Then iter this process to whole image. So the task is how to use per block pixels value(60 ...
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Why $P$ and $Q$ don't exist on the same coordinate, they need to be reconciled (processed) to exist on the exact same cells in order to calculate RMSE

I have a question about the root mean square error and Wasserstein distance on the paper https://arxiv.org/abs/2111.08736?context=stat. Consider two discrete probability distributions $P=\{P_i\}_{i=1}...
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Significance test for an image centroid

I have an n x n matrix. Each cell contains a value. The matrix is essentially a heatmap. The null hypothesis is that the greatest values would be at the horizontal and vertical midlines of the matrix. ...
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How to develop Multistage classification model using deep learning

I am little confused while doing multistage classification using deep learning model. I have data as below: ...
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Where can I find pre-trained fully convolutional neural networks? [closed]

I know that fully convolutional neural networks can be used for classifying images of arbitrary sizes. I would like to use some pre-trained fully-convolution neural networks for extracting features in ...
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Image generation with multiple images as inputs

I am fairly new to machine learning. I am trying to generate a new image from other images of the same shape. An example of the image I'm trying to generate is an Hi-C data matrix: https://encrypted-...
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Probability of sampling >50% "bright" pixels from an image

Suppose an image consists of 300,000 pixels. 51% of these pixels are bright and 49% are dark. We are trying to determine if the image is bright or dark through sampling (in this example it would be ...
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Normalizing features for CNNs and out of distribution

As I was reading this question on another thread: Why normalize images by subtracting dataset's image mean, instead of the current image mean in deep learning? I realize that either one point is ...
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Testing for constant mean (stationarity)

I have a grayscale digital image with noise and I would like to test for uniformity in small neighborhoods. One hypothesis says that the mean is independent of the spatial coordinates, against the ...
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How to perform image classification in a dataset of images with heterogeneous sizes?

I have a dataset of images with very different sizes (ranging from 100X100 pixels to 5000X1000 pixels) and aspect ratios. I want to use neural networks for dealing with this problem. Is there any ...
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What are some of the commonly used image processing techniques for multiclass image classification?

I'm working on multiclass skin disease image classification(caused by bacteria and fungus). Some of the sample images are shown below. Images contain different background as shown in image_1 and ...
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Which network to segment a rectangle on the ceiling of a room (enclosed by joists), and taking advantage of prior knowledge

I am wondering how you guys would approach this problem. Given an image from a camera pointing towards the ceiling of a room (some joists are present), I want to segment the biggest rectangular area ...
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Strategy for Train/Test-Split on Video Sequences

My dataset consists of 15 video sequences, each sequence showing a different movement. I want to train a CNN to detect poses (e.g. standing, sitting, ...) on single frames of this dataset but struggle ...
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Structure from motion approach to estimate target frame from nearby frames

My question comes from the paper: https://arxiv.org/pdf/1704.07813.pdf , which is an unsupervised learning approach for depth estimation. Suppose I have a sequence of images $I_{t-1}, I_t, I_{t+1}$. I ...
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Finding a dataset for a computer vision project related to medical imaging (related to cancer/tumor) [closed]

I am trying to find a dataset of medical images related to tumor/cancer, there should be images different stages of the cancer and also preferably the details about the patient, their medical history, ...
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Image-recognition model makes good predictions only with training examples

Im trying to use a kaggle dataset to train a model that recognizes american fingerspelling language from an image. The problem is that, built the model, if i record the screen with the examples ...
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Really poor result using transfer learning on medical images vs on bees/ants dataset

I am using an Inception V3 model pre-trained on ImageNet and when I train it on Bees and Ants dataset from PyTorch training, I get this result: Dataset statistics: ...
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About basic understanding of attention mechanism and model weights

In the image domain, for a given image, suppose that we want to understand if there is a bird on that image (0 and 1 label = no bird and bird), attention mechanism helps to pay more attention to the ...
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No overfitting but bad prediction

I classified some medical images. And distribution of the dataset is : 494 Train Anormal 469 Train Normal 37 Test Normal 64 Test Anormal 84 Val Anormal 37 Val Normal ... My training result is (by ViT):...
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What should I do with Images that has no objects?

I have a dataset that contains images that has cancerous nodules. I want to use object detection models to detect these nodules from the image by using an object detection model. Now my dataset has ...
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How to get the probability a prediction is correct from a binary classifier

I have an image binary classifier that where class a = 0 and class b = 1 When I receive a prediction of a single image, is working out the probability that the prediction is correct as simple as: a: ...
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Classifying the relationship between two objects in an image

Let's say I have a photo of a group of people, and some of the people are pointing at each other. I'd like to train a machine learning model to detect two things: Which people are pointing For each ...

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