Questions tagged [segmentation]

In marketing/economics, the task of dividing some population such as customers into sub-groups based on some type of shared characteristics or demands. Statistically, various unsupervised and supervised methods may be used for that (clustering, conjoint analysis, tree, etc.).

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10 views

Improving bounding box IoU for document segmentation

I have tried using RCNN and faster RCNN to detect tables and paragraphs. However, I keep encountering the same issue, which I guess is because of region suggestion algorithm; Parts of the first or ...
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106 views

Multivariate change point detection with strongly correlated (nonlinear) variables

I have a two-variable time series. There is a very strong nonlinear correlation between the two variables, so they can be thought of as: variable_1 = $X$ (random variable) variable_2 = $f(X) + N(\mu,...
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Is the capacity of a multitask U-Net with two-decoders the same of a standard U-Net with doubled capacity in the decoder?

I implemented a U-Net with an additional decoder (one encoder, then it splits into two decoders). The first decoder predicts the normal segmentation label and the second decoder predicts the distance ...
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Looking for classic image segmentation tool for small RGB images (python)

I am working with 32x32 colour images and want to segment items on them. I am using https://scikit-image.org . This only seems to work on grayscale images and mainly seem to focus on detecting edges ...
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40 views

Meaning of sparse annotation for images?

what is sparse annotation? Is it pixel-wise labeling for images. what are the other types of annotation?
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Grouping already known objects from an Image

Assuming my typical training data are images that each contain multiple animals, with the animals themselves already located/segmented (We have information for each pixel whether it is an animal or ...
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226 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 ...
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Krippendorff's Alpha for unitizing texts

I have a question about using alpha to measure Krippendorff's inter-annotator reliability in qualitative data. After reading the papers, I'm still not sure how to handle this case. I'm working on a ...
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what is the best approach in dealing with large dimension custom data for training and predicting deep learning models

i am trying to implement semantic segmentation for satellite images.My custom dataset has dimensions(height,width)in range (3000, 3000)what is the best approach for feeding(for training) and ...
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Approaches for a “risk segmentation” applied to auto insurance

I wonder about approaches for a risk segmentation applied to auto insurance. i.e. Suppose I have all the states within United States, and I wanna say: "Ok, Alaska and Alabama belong to group 1; ...
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Modeling on entire dataset vs. Combining segmentation models trained on subsets of the same dataset

Training machine learning models on an unbalanced dataset: about 3% positive labels, and 97% negative. The modeling goal is to get as many examples as possible with 60% precision on a holdout test set ...
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Deciding length of units in sound recognition for training HMMs

I am working on creating a method to detect changes from one song to another. Namely, I hope to use a Hidden Markov Model (HMM) in order to model a part of a song and check to see if it accurately ...
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How to include percentage variables in PCA + K-means when some values are undefined because the denominator is 0?

I'm trying to do customer segmentation by using PCA to reduce dimensionality and then feeding the resulting principal components into a K-means algo to get at the final segments. Some of my variables ...
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Training neural network with a single instance at a time

For a semantic segmentation problem attempted using neural networks, does it make sense to try achieving overfitting with single training example and then (depending on generalization error) add more ...
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How to find categorical contributing factors for an anomaly?

Given a house sales dataset with number of houses sold each day and their attributes (i.e., price, number of rooms, size, etc.) - if on a specific day there's a spike/drop in sales, what are some ...
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Multiclass Segmentation Using U-Net: My training loss is not decreasing after certain epoch (accuracy not increasing) [duplicate]

So the problem is to perform a multiclass segmentation (255 classes of crops), and I am using a U-Net model for that. The input images are grayscale and the images of dimensions (128,128,1) are ...
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How to use Bayesian belief Network map/Causality map for segmentation?

I have obtained the causality map for my data. I have an event of interest and the evidences for the event. How do I make the use of this information to come up with segmentation/clustering such that ...
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What methods could/should I use for identifying sub-groups in a customer segmentation?

I am working on a segmentation model that has been fed into the company by an external agency which created the segmentation based on surveys. I have a number of 6 attitudinal segments and after ...
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How we determine the ground truth box of the object in each frame in Matlab?

When we track one object in a video sequence using a tracking object method, the estimated bounding box is given by the method for every frame of the video. But how we determine the ground truth box ...
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243 views

Multi Label Semantic Segmentation - One class is way behind

I'm trying to build a Multi-Label Semantic Segmentation model, but while training, when I'm looking at the validation set, I can see that one label is far far behind, and in the end, he is not getting ...
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82 views

How to make 65 clusters ? Is k-mean good algorithm to do this?

I am trying to segment customers based on demographic, behavioral, lifestyle etc into 60-65 segments inline with Claritas Prizm segments Link1 Link2 I have 1 million records and 264 variables. ...
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380 views

Customer Segmentation Using RFM Interpretation of Negative Scaled Variables

I am doing customer segmentation using RFM. Prior to proceeding with the clustering, I log transformed my Monetary variable to account for skewness. ...
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How do I run a cluster analysis on customer store visit data to identify clusters that consist of both location and time?

I have data from customer visits to a number of different stores over the course of a few months. In one column I have the time/date of the visit, in another the location of the visit, and in other ...
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291 views

Customer-Segmentation based on feature importance

The problem: We have asked customer-satisfaction for various shops (variable satisfaction ranging from 1 to 4). In addition we have provided 30 shop features and our participants had to rate if the ...
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58 views

Conceptual question on image pattern representation

I have a basic question regarding pattern learning, or pattern representation. Assume I have a complex pattern of this form, could you please provide me with some research directions or concepts that ...
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Error in an article with a conditional probability?

I’ve recently read the article "Visual Tracking of Human Visitors under Variable-Lighting Conditions for a Responsive Audio Art Installation," A. Godbehere, A. Matsukawa, K. Goldberg, American Control ...
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biological fluorescence supervised machine learning [closed]

Some general questions... So it appears with most classification learners one must come up with a series of quantifiable variables to associate with each observation. This might include mean and std ...

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