Questions tagged [machine-learning]
The machine-learning tag has no usage guidance.
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How to draw a phase diagram in MATLAB (picture attached) for 3 variables (x, y and mean squared error)?
I am trying to make a phase diagram for three variables .
a=[0.01 0.5 1 1.5 2]; b=[0.1 1 2 5 10];
and their mean squared error value in variable 3 (having 5 rows and 5 columns)
mse =
...
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What architecture of CNN to solving a image regression problem (case study: solving Poisson equation)?
I've been working on solving Poisson problem using CNN model (you can ignore Poisson problem part if you not familiar and jump to image processing/CNN part). More specific, I am solving electric ...
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3
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Measures of "coincidence"?
Assuming I have two sensor feeds, is there an algorithm that gives an estimate of how likely it is that they point at/derive data from the same scene (possibly from different angles, with different ...
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How to normalize(or other) the audio data so that the same labels with the similar characteristics from different records?
I am trying to detect swallows from recordings taken from hospital. I manually labelled the recordings on the Praat. Now the valid labels are silence, swallows and nonswallows(noise, enviromenment ...
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How do I know if an Image contains Noise?
I am working on a set of Images captured by an Industrial camera. However, I am not sure if I need to apply any Denoising (e.g. Gaussian or Laplacian etc) on it ?
Is there any metric that I can used ...
- 101
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2D Fourier transform normalization/standardization for machine learning
I am training deep learning models (i.e., CNNs, convolutional deep neural nets) on Fourier transformed images, i.e. the neural net receives as input a 2-channel (real and imaginary) tensor of shape e....
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preparing the ct scan data of a patient, using a visible feature in the mri image
A dataset of mri and ct scan images of patients has been prepared. There is a feature /damaged area/ in the mri image that is easily visible. But the injury of this area is not visible in the CT scan ...
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Find rows that meet all criteria in SQL
I'm unable to create a SQL query that does the below:
Say for instance Person A participated in Event 1 and Event 2.
Person B participated in Event 1.
Person B participated in Event 1 again
Person C ...
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58
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Calculating satellite position from images taken by the satellite of the earth surface
I'm currently a little stuck with a problem, that sounds easier than it is (at least for me):
Let's say you have satellite images taken from LEO that show an approximately 1000 km wide area (the image ...
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Using Soft Labels in Classification Models
(Updated)
I am working on a classification project in which I am required to detect a component of a railway switch using time-series data collected from an inductive sensor.
After some signal ...
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Why is pitch detection an ongoing research field if it's solved by mel spectograms?
I'm relatively new to DSP so excuse my ignorance but I was hoping to have an audio related question I had answered. If we're able to decompose audio into frequencies (e.g. mel spectogram) why is there ...
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Nuclear norm minimization of convolution matrix (circular matrix) with fast Fourier transform
I am reading a paper Recovery of Future Data via Convolution Nuclear Norm Minimization. Here, I know there is a definition for convolution matrix.
Given any vector $\boldsymbol{x}=(x_1,x_2,\ldots,x_n)^...
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ICA and Gaussianity: A Misleading Example in the Book Konstantinos Koutroumbas, Sergios Theodoridis - Pattern Recognition
A book reports that ICA cannot be used if the independent components of the analyzed data are Gaussian (at most one can be Gaussian, but no other). However, in the same book, the following example is ...
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Relationship / Connection Between Machine Learning / Deep Learning and Computer Vision [closed]
What is the actual relationship between Machine learning and Computer vision? Is Computer vision is subset of Machine learning or is it another independent subset of Machine Learning? I am trying to ...
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What is the Relationship between signal processing and machine learning? [duplicate]
What is the relationship between signal processing and machine learning?
Is signal processing necessary or helpful before learning Machine learning?
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Use the mean and standard deviation after MFCC extraction
I've noticed in some literature that the authors chose to use the mean and standard deviation of the extracted MFCC features.
"ANALYSIS AND VOICE RECOGNITION IN INDONESIAN LANGUAGE USING MFCC ...
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Is it okay to include "Machine learning" in Digital Signal Processing labs?
I teach a Digital Signal Processing Lab to Electrical Engineering undergraduate level students. We have most Labs on MATLAB and some Labs on a dsp kit tms320c6713. I am planning to incorporate topics ...
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How to identify sudden changes in signals?
There are instances when neural networks, after being trained continually on a subset of data, tend to drastically lose their performance. I've attached an image below depicting the same. I am looking ...
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Why is automatic modulation classification hard?
There is a huge amount of research into automatic modulation classification (AMC) using machine learning.. Why is AMC a hard/difficult problem that we need to use machine learning or even deep ...
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Comparison of two ways of speaking
I have two audio files. The first one is like I would like to speak (reference). A little bit slower but the constant pace, good pronunciation, etc. The second one is various recorded audio files. I ...
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Standardize MFCCs Before or After Computing Deltas?
I want to create a feature space that includes MFCCs, MFCC deltas, and MFCC delta-deltas concatenated along the time axis which I will then feed into a CNN for speech emotion recognition.
After ...
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How to decided the score threshold in speaker recognition?
I am new to speaker recognition and now starting from the GMM-UBM algorithm.
Say I have a pre-trained UBM and speech from target speakers ...
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59
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How to modify spectrograms so that there is no effect of amplitude on their classification?
Is there any way to bring different classes of spectrograms to comparable amplitude levels so that when they are used for classification, the deep learning algorithm focuses on other aspects (like the ...
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937
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A Machine Learning Based Algorithm as an Alternative to the Matched Filter
Consider we have to detect a known signal added with Gaussian noise. In this scenario, the matched filter is known to be an optimal filter for SNR. The question: is there any machine learning ...
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Mapping ground salinity in UAV images
I have a plant field with potatoes. I have made measurements on ground with a sensor and I have measured soil salinity (Electric Conductivity) and I have min EC and max EC. I have also UAV images of ...
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Classifying 2 Classes of Ultrasound Signal Using Machine Learning by Frequency Domain
I have two samples which, when exposed to ultrasound, emit their unique frequency responses. As can be seen in the attached figure, where the exciting frequency is 2.25 MHz, sample 1 emits a strong ...
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Building a Pipeline for Image Classification / Clustering Tasks with Features Extractor and Dimensionality Reduction (Example on MNIST Data)
In MNIST, there are 28x28 images of hand written digits.
What features would one extract in order to classify then without any Deep Learning involved?
How does Dimensionality Reduction get in the ...
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355
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Image Clustering Using Linear Discriminant Analysis (LDA) Compared to t-SNE / UMAP
This is a a continuation of the discussion from Unsupervised Clustering of Images.
Image that we have MNIST database and we want to separate all the images like this. But we want to use Linear ...
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Unsupervised Clustering of Images: Which Algorithms?
Given a set of images $ \left\{ \boldsymbol{x}_{i} \right\}_{i = 1}^{N} $ how could one cluster them in an unsupervised manner? What are the useful features / tools to do so?
For instance, will ...
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Image Segmentation Using Deep Learning
I see in many reviews on Autonomous Car how they segment the images with person, cars, etc...
How is it achieved in Deep Learning?
Could anyone give an example of that?
How it is done?
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Which Programming Language Should Be Used for Deep Learning (Deep Neural Network [DNN])?
I will do voice activity detection and speech enhancement based deep neural network. However, I don't know whether to do this via matlab or pyhton. In which programming language can I find more ready-...
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Can machine learning extract two source signals, given a mixed signal?
I have two signals from two sources at a given condition and I have a mixed signal at the same condition that I know is coming from those same two sources. Is it possible to extract the source signals ...
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Explain the Process of Spectral Pooling and Spectral Activation in the Context of CNN in Frequency Domain
I am reading the paper Design of an energy efficient accelerator for training of convolutional neural networks using frequency Domain Computation:
which uses Frequency Pooling, from Spectral ...
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Cocktail Party Problem with a Single Signal of Data (Single Mic)
I have been doing some multimodal signal analysis, and sometimes ICA is used for detecting statistically independent components.
From my understanding, say if you have 2 sources and 2 receivers/...
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I have two signals, recorded from the same device. How do I standardize/normalise them?
I essentially have two signals X and Y, recorded with PPG devices. These have been filtered already. I want to standardize(z-score) or min-max scale them but I don't know if I should do this on each ...
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Signal patterns between train and test sets are vastly inconsistent
I am trying to build a machine learning classification model of a given signal dataset of 3 classes (one file for train signal data is another one for test data). I tried different machine learning ...
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Is it possibel to use CNN to bandpass signal?
I have a time serie dataset and want to train a CNN-LSTM model to predict as well as detect outliers. How can I use CNN to filter the signal and extract features from specific frequency band?
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What image augmentations can help a neural network identify the lowest-value pixels within an image?
I am training a CNN to identify objects, and I believe the network will learn much faster if it can learn to focus on the pixels with the lowest value. One way to go about this would be to augment the ...
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Modern Method for 1D Signal Segmentation
I want to segment a signal in an unsupervised manner.
The data is a 1D signal which has different segments which I want to be able to segment automatically for farther processing.
I am looking for a ...
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The Meaning of $ \mathbb{E} $ Operator in the Pix2Pix Loss Formula of a Neural Network / Convolutional Neural Network
I've been observing the Pix2Pix Paper - Image to Image Translation with Conditional Adversarial Networks and wondered on formulas. For example, the objective of the CGAN is:
,
where x - observed image,...
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References of deep learning and ai for dsp researchers [closed]
Are there excellent references for machine learning, deep learning and ai for DSP researchers?
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Backpropagation in a Network [closed]
Hi does anyone know how to solve this. Im really struggling to figuring this one out.
I am unclear of how the backpropagation part would work in this network and how to calculate it for each weight. ...
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Power Spectral Density as a single number confusion
I'm trying to recreate the results of a machine learning applied to the DSP classification in the article: link.
I have a signal (activity measurements from a smartwatch) per patient, so about 30 ...
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Can a linear reconstruction in compressive sensing perform well?
I am trying to implement compressive sensing for grayscale 2D images, then reconstructing them using a multi-layer perceptron(MLP). It seems to perform well no matter how many layers I add or remove, ...
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Recommendation for courses / studies on digital signal processing
I hold a master's degree in mechanical engineering. However at my job I am more and more diving into topics of signal processing and data science. I find it great to discover about new topics and to ...
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Using STFT as an input to a Neural Net
I'm trying to use the STFT as an input to a neural network. After flattening, there are over 4,000 features for a few seconds of audio. Is there a recommended way of summarising these to be a more ...
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a neural network approach for FIR filter
I am trying to write a code for a neural network to do the digital filtering on some signals. Is there any neural network model for digital filtering?
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Help with denoising signal and periodogram analysis resources
This is a cross posting from the crossvalidated stack exchange as I thought this may be a better forum to ask.
I have a dataset consisting of respiratory time series signals of different lengths ...
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Upsampling vs downsampling. Which to use when?
Downsampling reduces dimensionality of the features while losing some information. It saves computation.
Upsampling brings back the resolution to the resolution of previous layer.
My question is which ...
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Finding arbitrary/random repetitive patterns in signals (both self and across two signals)
I am trying to figure out a direction for my research. I need to find random repetitive patterns between two signals and on each individual signal. I have read about FFT and time series-motif ...
