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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Which image format is better for machine learning .png .jpg or other?

I'm trying to train a neural network with images. Since I'm extracting images from a video feed I can convert them either to .png or .jpg. Which format is preferred for machine learning and deep ...
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18 views

Analysing arrays of image data with Machine Learning Models

I am trying to do Machine Learning on arrays or vectors describing images. The target variable is a category I am trying to predict. I have multiple features that each contain arrays describing the ...
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How do you train a model on a dataset that's unlabeled but we know the percentage of every class?

Say we have a data set that's pictures of apples and oranges, but we don't know which is which. However the data is organized in such a way, that for some groups of images we know how many of them are ...
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Is it possible to determine a certain characteristic point in a picture based on existing pictures?

The problem I try to solve is actually something I want to apply to an existing use case. To give some background information on that, there's this site botb.com that works kinda like a lottery, ...
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Is GAN effective enough to replace data augmentation and manual annotation?

We all know that GAN can be used to augment and expand our dataset Can a GAN be used for data augmentation?. But my question is, is it effective and fast enough? For example I have done experiment ...
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Cropping input images Neural Networks

I'm creating a simple neural network for image classification,I had some doubts about the input images. Let's suppose i'm trying to classify (for example) a bear and i have an input image like this: ...
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21 views

Finding function for histogram to investigate on minimum, maximum and inflection points

To investigate on the statistics of an image, I want to find out how to get all 1.) minima, 2.) maxima and 3.) inflection points for the histogram of a specific image. I know how to extract the ...
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13 views

why encoder/decoder is better than stack of conv layers in segmentation task? [closed]

I have read through several articles that said stacking of conv layers consume lots of computer resources(I guess only run time not memory right?) https://www.jeremyjordan.me/semantic-segmentation/. ...
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Is there a difference between training with multiple objects in a single image and multiple objects in a different images?

I'm trying to generate data for my object detection network (which will be used for TensorFlow: ResNet). What I'm currently curious about is this: if I have the same total amount of data (each data ...
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27 views

Average precision biased in object detection when validation set has easy examples

I am computing average precision (AP) for object detection as in Pascal VOC dataset. Sometimes my results were too good to be true and I suspected that I might overlook something. Then I realised that ...
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30 views

Is there a model or algorithm to improve digital drawings?

given a bad drawing, the algorithm should deform the edges of the bad drawing and fill them with color so that it looks more like a learned character. the entry would be a very poorly made drawing of ...
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Compressing an image using neural network

I've recently given several attempts to compress an image using neural network. The approch is to treat a trained neural network itself as a compressed data. I was expecting that, given x,y as input, ...
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21 views

how to choose the number of patches in sub-region classification before appling CNN?

I'm currently working on image classification, i want to divide the input image into sub-regions(patches) and apply a deep convolutional neural network (CNN) to train and classify each patch ...
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How to enforce smoothness in guided image filtering techniques ? Any preferable model?

Which one (or more) of these three minimization models is the appropriate way to enforce smoothness in guided filtering framework ? \begin{eqnarray} %\begin{aligned} & \sum\limits_{q \in {N}(p)} {\...
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1answer
17 views

Is it possible to train neural network to generate similar pictogram?

Is it possible to give the neural network and pictogram and train him to generate variant of this picto? I know there is some initiative to generate vectors drawings like https://github.com/...
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7 views

Fusing label distribution and on-hot encoded labels

A while ago I came across a paper for image classification that utilized both label distribution and one-hot encoded labels to classify images. An image has a label distribution for all classes (4 ...
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What statistical analysis to use to relate multispectral seed data to other conventional tests?

I'm a PhD student at the University of São Paulo, Brazil, and I'm conducting experiments with multispectral analysis of soybean seeds. I have reflectance data for 8 different soybean seed samples, ...
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1answer
4k views

How does a simple logistic regression model achieve a 92% classification accuracy on MNIST?

Even though all the images in the MNIST dataset are centered, with a similar scale, and face up with no rotations, they have a significant handwriting variation that puzzles me how a linear model ...
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Using CNNs for template matching in multi-channel image?

I was wondering if it's possible to train a CNN to recognize similar parts between different images. Here's my problem: let's say I have different images that overlap in part to form a larger image (...
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Label smoothing for sequential image classification

My data are images of a car moving in a virtual environment, each example is classified as "left", "right", "straight", depending on the steering direction. I have a class imbalance, most of the ...
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decision tree for binary image classification

For a quality inspection task, I need to inspect whether the soldering on a PCB are passing or not. The soldering are at 3 soldering pads that are square shaped. See below. As you can see, there is ...
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1answer
24 views

How to apply fuzzy membership function to binary images?

I'm implementing this paper "Neural Network-Based Edge Detection for Automated Medical Diagnosis by Lu et al" and it says it uses a fuzzy membership function to improve its generalization accuracy. ...
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1answer
12 views

How to compare different data preprocessing when using CNN from sratch

Let's says you use a CNN for image classification. You have binary images: pixel values = 0 or 1. Some tools can be used to get those images with continuous values (i'll not explain how since that ...
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1answer
9 views

Intensity normalization with segmented ROI on black background

I have a set of segmented ROIs .jpgs against a black background. Pixels in the ROI range from 0 to 255 in grayscale (1 channel only). I want to normalize these intensities in order to feed it into a ...
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22 views

Does the TensorFlow object detection API understand the idea of “context”?

For example, if I'm creating an object detection model to recognize forms of transportation (cars, bikes, planes, etc.). If I also train it to recognize wheels, will it be more likely to detect wheels ...
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25 views

YOLO architecture clarifications

I am trying to train a YOLO model to draw bounding boxes around individual handwritten words. I don't need the network to classify them and I don't need the words to be in order either. I would have ...
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24 views

Can I train a CNN with a large number of input channels (more than 3, RGB)?

The input of the first layer would be composed of N channels and each input sample would look similar to this image (each plot is a channel) The label would be a number for each channel. The train/...
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23 views

Neural network to regress peaks in an image does not converge [duplicate]

I am trying to predict the position (x,y)-coordinates of 16 peaks in an image. The images look like the following: The green dots are the true peak locations and the red crosses represent a ...
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60 views

finding Human dimensions from photos

I'm working on a problem where I have to extract different human parts real-world dimensions ( waist width, arm length ) from photos where there are front and side photos, the given values are the ...
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Data balancing in image classification

I've to segment defects from an image. The image consists of only tomatoes with it's defects in it. The defects and tomatoes in the dataset are as follows: ...
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8 views

Finding objects in an entanglement

I'd like to know if there are ways to solve entanglement problems like this one: Given a known shape (in red), can a machine locate (or at least count) the instances of this same object in an image ...
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9 views

What are some line feature extraction tools?

I hope to find a feature extraction tool/method that specializes in extracting the features of a line, such as length, curvature, etc. Are there any such tools? The ones I found are image processing ...
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7 views

Strange results when computing the HOG and histogram intersection similarity

I am trying to re-implement algorithms mentioned in this paper to measure the "naturalness" of one synthetic image, given a real image. The algorithm seems straightforward, basically we have two ...
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1answer
50 views

variable number inputs to CNN

I am very new to deep learning and image recognition. Please let me know if my question needs more information. In the image recognition problem I am trying to solve, we are supposed to develop a ...
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Coming up with a metric that measures “homophily”?

[I'm not sure if this question goes here on Stats.SE --- please move if not.] Consider a 2D unit square. I observe N red and M blue balls on the square. I want to come up with a metric that measures ...
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1answer
18 views

Using one neural network for each image type

I have been reading about Convolutional neural networks and its use in image recognition. Most of the examples I have seen so far train one single network to classify an image into one label or class. ...
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Passing specific achors to YoLo training process

We are trying to improve our YoLo algorithm results of recognizing one class of varying sizes (~ varying distance to the camera). Luckily, the a priori position of the object is known with a certain ...
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1answer
39 views

CNN architectures for predicting next frame

I am currently trying to generate image of a body tissue at time t+1, by using image given at time t (or t-1,t-2...). Until now, I experimented on some Incomplete Conv Autoencoders in two main ...
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1answer
39 views

Stars and Machine Learning

Ok So I have been dying in interviews lately. Need to Brush up more. Maybe you can help me with this interview question (multiple Choice). If you tell me good sources to look at to learn more about ...
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22 views

Time complexity for locality sensitive hashing similar image search

I am trying to find most visually similar images for large image dataset. (N=1 million), using LSH (Locality Sensitive Hashing). Image feature vectors are 4096 dimensional VGG-16 features. Now, my ...
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Statistical Significance of a 3D Volume

I have two 3D volumes of a single patient. One 3D volume before surgery and one 3D volume after surgery. The 3D volumes are MRI images (Mangetic resonance imaging). Each 3D volume has dimensions [100, ...
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1answer
118 views

Increasing image size in pytorch celebrity generating GAN? [closed]

complete newbie here, bear with me. I'm making my way through this tutorial: https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html Upon attempting to make a simple change to the image ...
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23 views

What are the time complexity of image feature extraction algorithms, including HS, HOG, MSER and SIFT?

Can somebody help me by writing me a time-complexity of each image feature extraction algorithms. Especially I am interested in Harris-Stephens(HS) corner detection, Maximally Stable Extremal Regions (...
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85 views

Why is my keras resnet50 model overfitting? [duplicate]

I have applied Keras ResNet-50 on a small x-ray image dataset. I tried making layers both trainable and non-trainable, but my model validation accuracy doesn't improve above 50%. I don't understand ...
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53 views

How to reconstruct an image from a training set?

Description: I have taken a series of images/photos of a panorama from different positions (x,y) in space pretty close to each other (max 100m difference). Here there is a top view representation to ...
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218 views

Principal component analysis on RGB images

I've implemented a method to compute PCA on grayscale images. I haven't seen PCA on RGB images yet, which left me wondering if it is possible to perform it. With RGB images, is PCA done for each color ...
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25 views

Estimate Particle Density from Image Analysis

Suppose I have an old image of an object where the objective is to estimate the mean particle density of said object. Using a software called ImageJ, I am able to run a thresholding algorithm to ...
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An Interesting Model with Unknown Orthogonal Design Matrix

Consider a linear mixed model, $$\mathbf{y}_{ij}=\mathbf{\Gamma}\mathbf{\mu}+\mathbf{z}_i+\mathbf{e}_{ij}, ~~ ~~i=1,\ldots,m,~~j=1,\ldots,n_i, $$ where $\mathbf{y}_{ij}$ are $k\times 1$ observation ...
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122 views

What is the best way to normalise image data?

The normalisation in an image really confuses me. I mean there are multiple ways to do it (see below) but, is there the best one, or most preferable one, or one needs to experiment with all to find ...
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187 views

Does Sørensen–Dice Coefficient (Dice Score) only account for true positives?

I'm working in a project on medical image segmentation which uses the Dice Score as part of the loss function, but I got some doubts with the commonly adopted implementation. The definition of Dice ...