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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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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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15 views

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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1answer
24 views

Deep learning models for unsupervised semantic segmentation

I am working on semantic segmentation for satellite images using keras and python. It is my understanding that popular models like U-Net require mask images (labels). Are there any unsupervised deep ...
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8 views

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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23 views

avg loss values increase during training dataset [duplicate]

I have setting up a project that should detect iris region ( in eye ) in real time using deep learning , I have cloned yolo segmentation project in github : https://github.com/ArtyZe/yolo_segmentation ...
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7 views

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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1answer
25 views

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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2answers
22 views

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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22 views

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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32 views

How can I isolate objects from a 3D image volume using normally distributed geometric features

I have '.tif' image stacks that I am analyzing as volumes. For every object, I can get the Volume, surface area:volume, 'sphericity' and Euler number. For every one of those features, the objects I am ...
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1answer
20 views

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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40 views

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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14 views

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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1answer
22 views

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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0answers
54 views

Why has the Auxiliary loss fallen out of favor?

Why has the Auxiliary loss fallen out of favor? In deep learning, at one point, there were many deep models that utilize multiple softmax loss so that the gradient can flow better at the beginning of ...
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1answer
29 views

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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29 views

Detecting the bounding box of an object in an image?

I have a dataset of images . Each image has an object in it. In a seperate csv file , I have been provided with the coordinates of the bounding box for the object in the training images. How do I ...
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1answer
55 views

Detection of music note sequence in audio signal

I have an audio signal which contains the combination of different western music notes(I know this combination in advance) and I want to identify the sequence of the music notes present in it. For ...
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3answers
499 views

Strategies for time series forecasting for 2000 different products?

First of all, I realise that my question is very broad and that it may be hard to answer this question because of it. Do you have any advice on how to approach a 'problem' where you need to make ...
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1answer
40 views

Future of statistical methods in image segmentation? [closed]

I was looking for a purely statistical method for image segmentation and found many, e.g. Hidden Markov Random Fields with EM algorithm. But it seems to me that these methods are nowadays completely ...
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1answer
67 views

Introduction to Conditional random fields

I came across the application of a conditional random field (CRF) to the output from a convolutional neural network (CNN) for image segmentation. The additional CRF step seems to be a common ...
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1answer
94 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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8 views

Does it make sense to talk about over/under segmentation in a binary segmentation problem?

I was recently discussing with a college about thresholding a probabilistic map such that if the threshold is too low more pixels become part of the segmented area, and if it's to high there will be ...
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1answer
24 views

To segment or not to segment, this is the question

I am starting a project, in which I plan to run a neural-network regression using images. These are simple images of particles in a field with low contrast. The shape of the particles changes in ...
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0answers
57 views

Metric for evaluating predicted bounding boxes from semantic segmentation on an object level outside of training

Context For simplicity let us pretend we are performing semantic segmentation on a series of one pixel high images of width w with three channels (r, g, b) with n label classes. In other words, a ...
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0answers
19 views

Imposing independence constraints in mixture modeling of correlated data?

For 1-D signals (spectra) or 2-D signals (images), is there a way to impose the constraint that the data within a group is uncorrelated? I am iteratively applying background correction model fitted to ...
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0answers
9 views

Spreadsheet segmentation

I work on an spreadsheet segmentation/ml-based-parsing project. Input spreadsheets vary in shape and formatting to some extend. Goal is to transform any given spreadsheet into normalized database ...
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2answers
154 views

Why is it possible to train a semantic segmentation neural network like U-net/Tiramisu from scratch using small data-set like few hundreds

Why is it possible to train a semantic segmentation neural network like U-net/Tiramisu from scratch using small dataset like few hundreds. While for the image classification task, it is not ...
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0answers
432 views

BatchNorm after ReLU

I am currently experimenting with different settings for a U-Net (https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/) based image segmentation and I was unable to find out if it makes any ...
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0answers
51 views

Personalize Recommendations for small dataset

I'm working on a recommender system for a set of niche products. These are products that don't have a large number of customers. Does anyone have any tips on algorithms or approaches that work well ...
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1answer
29 views

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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0answers
86 views

Jaccard Similarity for matrices

I want to use the jaccard similarity to measure the quality of my binary segmentation. I found a function in the library sklearn.metrics called jaccard_similarity_score and I found in another forum ...
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0answers
72 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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0answers
330 views

Can I increase the accuracy of Unet by training on signal vs background (2 class) VS signal only (1 class)?

I have a Unet deep learning architecture, and it is working ok at detecting my signal, however, its accuracy is not sufficient for the purposes I am trying to use it. Let me show you an example: My ...
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1answer
25 views

Feature Identification for customer profiling

Problem: I want to identify the characteristic(s) of people who would shop on Monday vs Sunday (or any such dichotomous response variable). I have over a million observations and >50 variables/...
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1answer
91 views
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0answers
147 views

R - How to recover breakpoints from a “breakpoints” object [closed]

I have used the "breakpoints" function from within the "strucchange" package to find the optimum number of breaks and their points in time ready for the linear segmentation of a time series. I know ...
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2answers
298 views

customer segmentation with categorical variables

I have a customer dataset, which is a survey result. I have 1595 obs. and about 200 columns (200 because most of the cases the questions were multiple choice and we had to split it into columns). ...
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1answer
939 views

How to implement a weight map for a U-Net [closed]

I have a question regarding the convolutional neural network known as U-Net (see link below) and hope somebody can help me out. https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/ In the ...
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1answer
29 views

How can we model the visit pattern of a customer in a retail store?

I am trying to segment customers based on how recently they visited the store. However, I am also trying to incorporate the frequency with which they visit the store. For example, in a data collected ...
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1answer
1k views

how can my loss suddenly increase while training a CNN for image segmentation?

I work with keras 1.2.2 with a tensorflow 1.4.0 backend. I'm using a unet architecture, I have 708 images of 650x650 pixels and 6 chanels. I augmented the dataset with mirrorings and rotations, for a ...
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0answers
85 views

Hierarchical clustering on dependent data

I do customer clustering based on weekly data. I don't want to rely on only one week of data so I was considering pooling the data over a few weeks together and assume that these are simply "different"...
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0answers
308 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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1answer
63 views

Quantify whether a set of binary segmentation models (experts) have diversity on a fixed dataset?

I have a set of models for binary segmentation task (M=10), and a set of images (N=1000). I also can collect the prediction map for all these N=1000 images, resulting in 10,000 grayscale maps. Now, ...
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1answer
3k views

Cross cluster analysis of categorical data in R [closed]

How do we perform cross cluster analysis in R. Most of my data has categorical variables {variable Marital Status (married, single, divorced); variable Education (tertiary, secondary, primary, etc.); ...
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5answers
2k views

is K-Means clustering suited to real time applications?

I want to segment a sequence of RGB images (basically it's a video) based on their colors in real time. KMeans is an easy and intuitive algorithm to use in this case, but it's execution time is very ...
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0answers
59 views

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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1answer
1k views

Fully Convolutional Neural Network Exploding Logits and Loss

I am trying to train a fully convolutional neural network for 3D medical image segmentation, I have started from the architecture of this paper with the differences being that I have images of varying ...
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1answer
745 views

customer behavior analysis and segmentation using data from loyalty program

I'm trying to do some analysis on customers behavior. Basically, I have information on customer's loyalty points activities data (e.g. how many points they have earned, how many points they have used, ...
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1answer
36 views

Using pretrained segmantation network for unseen motives

For a research project, I need to do a segmentation on images. Since the motivation is nothing any of the big networks was ever trained on, I would ask if it still makes sense to use pretrained ...