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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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12 views

Cluster analysis with one attribute

I have a dataset of products and the price of each product. I want to perform clustering to group products of similar prices together. Would k-means clustering be appropriate? Is scaling of variables ...
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11 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
21 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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24 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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0answers
21 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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0answers
21 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
41 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
313 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
36 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
28 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
20 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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0answers
7 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
20 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
33 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
13 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
113 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
255 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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30 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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0answers
41 views

Analyse data from a survey with categorical data and likert scale questions

Good Day All, I am currently doing an internship in a digital marketing company. I was given a particular dataset to analyse, and its to segment the respondents of the survey. The main questions of ...
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1answer
28 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
69 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
58 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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288 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
19 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
84 views
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116 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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0answers
15 views

Customer data with mixed attributes

I know this is not proper question, but im kinda despair. I'm working on clustering for mixed data, and trying to make segmentation. But, it is difficult to get the data. Anyone has the data?
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0answers
12 views

determine willingness to pay for different customer segments given transactional data

Lets us say, I have transactional data of which products (with attributes) were purchased by which customer (with attributes) at a point in time. Are there modelling techniques to help me to determine ...
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2answers
248 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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0answers
46 views

Image segmentation review/survey

I'm looking for a recent review/survey paper on semantic/instance image segmentation. Could you please suggest any such papers?
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1answer
780 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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0answers
28 views

Detect/correct 2d slices outliers from 3d volume

I have to segment 3D volumes (240x240x155 pixels). I am doing this by segmenting 155 2D slices of 240x240 pixels with a CNN. At the end, I reconstruct my 3D volume by simply concatenating the ...
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1answer
27 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
800 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
71 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
283 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
57 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
54 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
692 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
419 views

Word Segmentation of Job Titles and then performing clustering on that segmentation

I have some user data that I'd like to cluster based on the job title of the user. For example, I have data that looks like this: ...
2
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1answer
35 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 ...
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1answer
430 views

Can U-Net be used for counting objects?

If I understand the U-Net paper correctly, the NN output is segmentation of known objects on the image from the background. In other words, the network will try to mark all the pixels which are part ...
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1answer
224 views

Optimal classifier or optimal threshold for scoring

In practice, there can be a classifier that gives far better performance at a specific acceptable threshold than an "optimal" classifier with better average performance across range of thresholds (...
2
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1answer
609 views

Machine learning to find an optimal set of parameters for a segmentation algorithm

Using machine learning to find an optimal set of parameters for a given segmentation algorithm. In the "classical" case of machine learning, in the training phase, the data set is constant and the ...
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0answers
232 views

Evaluate image segmentation with the absence of ground truth

Motivation: - Evaluate the computerised image segmentation against manual segmentation; - Evaluate the difference between difference manual segmentation. Background: Given a raw medical image (...
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1answer
187 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 ...