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Python: tune Least Squares Support Vector Machine (LS-SVM) With Gride Search Optimization

Iam looking for LSSVM with GrideSearch optimization in python, but could not find it. Scikit learn has SVM with Gride search but not for LSSVM. Please could you help Thank you
novin's user avatar
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0 votes
0 answers
13 views

Machine Learning for Image segmentation vs location identification

There are several machine learning architectures specifically devoted to image segmentation (like UNet). I am interested on identifying the location of an area but not interested in the precise ...
Filipe Pinto's user avatar
1 vote
0 answers
25 views

Wavelet Scattering features extraction

I want ask about the wavelet scattering feature extraction with machine learning -- if it is correct to use it for fault detection in induction machines?
Asli Farook's user avatar
0 votes
0 answers
8 views

What is the best approach when training and HDR model with LDR data?

I am working on this project "EMLight". Data: HDR Panoramic Photos y: Illumination Map of the Panorama X: HDR Croppings from the Panorama I want to make this project work with LDR photos, ...
xtc_'s user avatar
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1 vote
2 answers
80 views

lossy vs. lossless audio format in machine learning

We want to provide an ML model that recognises diseases from the voice. The feature extraction is based on a proprietary algorithm. Normally we have always used wav files. We keep asking ourselves if ...
Tütü's user avatar
  • 11
0 votes
0 answers
6 views

Feature for a signal classification

Consider that i have N signals of electricity energy consumption (from N different consumers) that ha 24 measurements over a ...
Murilo's user avatar
  • 113
1 vote
2 answers
73 views

System Identification vs Machine Learning?

Can we say that system identification is almost same thing as Machine learning or they both different techniques? I am confused because as shown in attached snap of matlab website, system ...
DSP_CS's user avatar
  • 1,870
0 votes
1 answer
64 views

What books describe convolutional neural networks for DSP?

(note: I read the site policy and meta questions about whether such a question is ok. I will be specific) I am looking for books that specifically cover using convolutional neural networks (CNN) for ...
HonestMath's user avatar
0 votes
0 answers
68 views

78RPM 1900's records - is there more in the high end signal than humans hear, and could ML extract it?

Consider some record with Enrico Caruso singing, anno 1904 or so. Back then, records did not employ pre-distortion such as with RIAA curve to then later, during playback, invert the curve, to get a ...
user1847129's user avatar
3 votes
3 answers
252 views

Resource recommendations to learn audio processing

I'm looking for some good resources to learn audio processing for a machine learning task based on classification of users as either 'COVID-19 positive' or 'COVID-19 negative' based on their cough ...
Anonymous's user avatar
0 votes
0 answers
101 views

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 = ...
Abeeha's user avatar
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5 votes
1 answer
102 views

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 ...
samueljohlal's user avatar
1 vote
3 answers
141 views

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 ...
2080's user avatar
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0 votes
3 answers
268 views

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 ...
StanGeo's user avatar
  • 101
0 votes
0 answers
57 views

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....
SheppLogan's user avatar
1 vote
1 answer
61 views

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 ...
Erfan Pot's user avatar
0 votes
1 answer
152 views

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 ...
Nuke's user avatar
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3 votes
1 answer
221 views

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 ...
Aisha Nasir's user avatar
1 vote
2 answers
286 views

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 ...
Mellow's user avatar
  • 111
3 votes
0 answers
85 views

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)^...
Xinyu Chen's user avatar
4 votes
2 answers
62 views

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 ...
volperossa's user avatar
5 votes
1 answer
98 views

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 ...
jkh's user avatar
  • 59
0 votes
0 answers
37 views

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?
DSP_CS's user avatar
  • 1,870
1 vote
0 answers
342 views

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 ...
Joe's user avatar
  • 113
2 votes
1 answer
341 views

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 ...
vbc's user avatar
  • 21
0 votes
2 answers
1k views

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 ...
desert_ranger's user avatar
1 vote
2 answers
95 views

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 ...
Pyfisch's user avatar
  • 145
2 votes
1 answer
138 views

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 ...
AlePouroullis's user avatar
0 votes
0 answers
60 views

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 ...
LCS's user avatar
  • 21
0 votes
1 answer
95 views

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 ...
nasrin's user avatar
  • 53
7 votes
2 answers
1k views

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 ...
Creator's user avatar
  • 88
1 vote
2 answers
175 views

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 ...
dsp's user avatar
  • 113
5 votes
1 answer
113 views

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 ...
nasrin's user avatar
  • 53
6 votes
1 answer
231 views

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 ...
euraad's user avatar
  • 405
5 votes
1 answer
603 views

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 ...
euraad's user avatar
  • 405
3 votes
1 answer
502 views

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 ...
euraad's user avatar
  • 405
1 vote
1 answer
161 views

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?
David's user avatar
  • 144
4 votes
1 answer
172 views

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-...
Zang Li's user avatar
  • 59
2 votes
0 answers
201 views

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 ...
NASRIN AKTER's user avatar
5 votes
2 answers
530 views

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 ...
Eduardo Reis's user avatar
2 votes
2 answers
118 views

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/...
NeuroEng's user avatar
  • 123
0 votes
0 answers
54 views

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 ...
Philippos Arkis Hadjimarkou's user avatar
0 votes
0 answers
32 views

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 ...
Dave's user avatar
  • 109
0 votes
0 answers
65 views

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?
Keivan's user avatar
  • 113
0 votes
0 answers
25 views

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 ...
desert_ranger's user avatar
1 vote
2 answers
2k views

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 ...
Mark's user avatar
  • 357
4 votes
1 answer
76 views

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,...
ans's user avatar
  • 173
0 votes
1 answer
56 views

References of deep learning and ai for dsp researchers [closed]

Are there excellent references for machine learning, deep learning and ai for DSP researchers?
Turbo's user avatar
  • 183
1 vote
0 answers
21 views

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. ...
get3low's user avatar
  • 23
0 votes
2 answers
290 views

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 ...
qalis's user avatar
  • 111

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