Questions tagged [noise]
The noise tag has no usage guidance.
32
questions
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0answers
35 views
Multi-task learning for improving segmentation
I am building a multi-task model, where my main task is segmentation and my auxiliary task is either denoising or image inpainting. The goal is to try to improve the quality of the segmentation with ...
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0answers
9 views
Deep learning model for very sparse object detection in noisy images
I am trying to build a model that takes in very noisy 200x200 greyscale images of spatially sparse objects and attempts to localise them with bounding boxes. The objects are very thin streaks (data of ...
0
votes
1answer
70 views
Using numpy to enter noise into data
I am new to data science and have to generate 200 numbers from a uniform distribution
set this as x and generate y data using x and injecting noise from the gaussian distribution y = 12x-4 + noise
...
0
votes
1answer
635 views
TypeError: __init__() missing 1 required positional argument: 'num_features'
I was trying to denoise image using Deep Image prior. when I use ResNet as an architecture i am getting error.
...
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0answers
14 views
Is adding noise the same as differential privacy?
I think I am getting confused about the difference to just add noise, and differential privacy.
I am trying to implement differential privacy according to this research paper:
https://ieeexplore.ieee....
1
vote
0answers
49 views
Model Tree M5 - Robustness to Data Quality Issues
I am currently investigating the M5 tree algorithm by Quinlan(1992) link here: https://sci2s.ugr.es/keel/pdf/algorithm/congreso/1992-Quinlan-AI.pdf
An example of a linear regression model of the ...
0
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0answers
3 views
Timeserieses Xi are noisy, and the noise depends on a timeseries Y. How do I remove that noise, to smooth the timeserieses Xi?
The noises in my timeserieses Xi are highly correlated on the timeseries Y. How would you approach the problem of removing that noise? Ideally I would like all the Xi curves to be smooth, as well as ...
0
votes
2answers
144 views
How to group every data point with HDBSCAN to some group to have no noise?
TASK
I am clustering products with about 70 dimensions ex.: price, rating 5/5, product tag(cleaning, toy, food, fruits)
I use HDBSCAN to do it
GOAL
The goal is when users come on our site and I can ...
1
vote
0answers
19 views
Denoising Prior to Image Classification
From what I have read, Denoising during preprocessing for image classification tasks seems to be a bit controversial.
While on one hand it might improve classification accuracy, the computational ...
0
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0answers
21 views
Finding clusters of 3D points where not all the points belong to a cluster
In my research, I'm trying to find clusters of brain activity, like in the following image:
Where the red dots represent the origin of the activity (where the green pole is the direction). So ...
1
vote
1answer
1k views
Choosing attributes for k-means clustering
The k-means clustering tries to minimize the within-cluster scatter and maximizing the distances between clusters. It does so on all attributes.
I am learning about this method on several datasets. To ...
2
votes
2answers
37 views
Which algorithm to use to identify clusters with a similar value?
Here, an example of my problem:
10000 observations of people with several features [age, gender, region, number of sons, ...] and a value to predict "income".
There is not a general relationship ...
2
votes
1answer
85 views
Methods for learning with noisy labels
I am looking for a specific deep learning method that can train a neural network model with both clean and noisy labels.
More precisely, I would like this method to be able to leverage noisy data as ...
2
votes
1answer
159 views
Remove noise by clustering on which step of pre-processing is better?
I am working on a classification task. The dataset is a UCI data set about machine learning with 200 observations and 2 classes.
Part of my model includes the following preprocessing steps:
remove ...
1
vote
0answers
26 views
Classification Algorithms For Noisy Problems
Dear fellow data scientists
I work in finance and have decent experience with neuronal networks. Right now I am facing a challenge where I need to classify a set of signals.
The data set looks ...
2
votes
2answers
775 views
If my model is overfitting the training dataset, does adding noise to training dataset help regularizing the machine learning model
I would like to know if this is a best practice or not. Can we add noise to the training data to help the model "fit less the training data"; as a result, hoping to generalize better on new unseen ...
3
votes
0answers
76 views
How to remove noise using morphological filtering
I have two groups of dots that both contain noise between them:
The line that separates the two groups in the picture is diagonal in shape.
I tried to use morphological filtering on this image to ...
1
vote
1answer
176 views
Noise Elimination with majority vote filtering
I have a dataset with label noise which I wan't to clean with majority/consensus vote filtering. This will mean I will divide the data in K-Folds and train an ensemble model. Than using the ...
1
vote
0answers
19 views
Isolated/noisy instances that have outsized effect on SVM hyperplane selection
Consider two linearly separable classes and the optimal separating hyperplane (image credit Prof Jiawei Han of UIUC):
Now consider if there were a single "rogue" point for the Yellow class - which ...
0
votes
1answer
2k views
what is correct way to perform normalization on data in Auto encoder?
working on anomaly detection problem. i'm using auto-encoder to denoise given input. I trained network with normal data(anomaly free). so model predict normal state of given input. Normalization of ...
3
votes
0answers
187 views
Training deep CNN with noisy dataset
I am training a Mask RCNN model with a train dataset that has been generated from some simple computer vision operations (color thresholding) and some morphological filtering.
The train set captures ...
3
votes
1answer
1k views
Effect of adding gaussian noise to the input layer in a CNN
I often come across Keras code that adds GaussianNoise to the input, however its not clear to me what advantages does it offer to the learning.
...
0
votes
1answer
1k views
How to create a complex Gaussian random noise with a specific covariance matrix
I am trying to generate a complex Gaussian white noise, with zero mean and the covariance matrix of them is going to be a specific matrix which is assumed to be given.
Assume i to be a point on the ...
0
votes
1answer
31 views
How can I avoid requiring global information for performing regression on meter variables?
Note: With a meter variable a timestamped value is the sum of all previous differences plus a difference to the most recent value. Think of a electricity meter counting the use of energy.
The goal ...
2
votes
1answer
107 views
Paramaeter estimation in noisy conditions with Machine Learning, possible?
Let's take two constants, $\alpha$ and $\beta$, both are given by two functions $f_1(\vec{\theta})$ and $f_2(\vec\theta$) (the model). These functions are known: we have an analytical closed ...
1
vote
0answers
235 views
Rain radar image noise reduction and cleanup
An application that I am building is plotting rain radar images on map. The images are transparent PNGs that are sourced straight from the local meteorological service.
As can be seen in the example, ...
4
votes
1answer
1k views
Training on accurate data versus noisy data
I have data currently available that is very accurate and I would like to train my classification methods on this set of clean data to learn the important markers for distinguishing between classes. ...
0
votes
1answer
59 views
Reducing noisy data from non normal distribution of data with std deviation?
I have used MATLAB code and get the two different row vectors A=1×18 and B=1×350. From both row vectors separately I need to remove the noisy data by using standard deviation. But the problem is that ...
3
votes
2answers
101 views
What is the loss function defined by Mnih and Hinton in their paper “Learning to Label Aerial Images from Noisy Data”?
In section 3.3 of the paper, they state that they use the cross entropy.
Then they define the probability for a label to be a false positive as $\theta_0$ and a false negative as $\theta_1$.
They use ...
1
vote
1answer
35 views
When we should use binning to redure noise? or How we find out we have noise?
I read several times which binning is helpful for reducing the noise of data. But how can we find out our data has noise? What if our data is clean and we reduce the accuracy of data?
Is there any ...
2
votes
0answers
87 views
Rprop is too noisy
Is there a way to reduce the noisiness and stochasticity of Rprop (and for that matter the iRprop+)?
Specifically, in deep networks (with 8+ layers) this effect starts to become apparent, as the ...
6
votes
2answers
5k views
Can Neural Networks be trained to smooth values / output the average?
Let's say we have a neural network with one input neuron and one output neuron. The training data $(x, f(x))$ is generated by a process
$$f(x) = ax + \mathcal{N}(b, c)$$
with $a, b, c \in \mathbb{R}^...
