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convolutional deep Neural Networks for matrix

I have a basic question about using convolutional neural networks. It's not my field but I'd like to read and understand about it. What I know that convolutional neural networks is used for image ...
Gze's user avatar
  • 640
3 votes
1 answer
107 views

How to Make Ground Truth Images for Document Image Binarization Task?

The two images are from DIBCO (Document Image Binarization Contest). The objective is to find a solution to binarize the top image (original image) to be similar to the bottom one (ground-truth image)....
Ksiau's user avatar
  • 31
0 votes
2 answers
394 views

Transforming RGB images including NIR to LAB

I'm relatively new to image processing, so I hope I don't ask trivial questions. I have some images that I want to use in a machine learning context. The images have four color channels: RGB and NIR (...
Dirk's user avatar
  • 101
1 vote
1 answer
71 views

Which Machine or deep learning algorithm is appropriate of this issue?

Suppose I have $n$ features as $Y$ = ($y_1 , y_2 ...., y_n$), and a matrix of $J$ of dimension $M$x$N$, one feature of $Y$ is selected randomly to be convolved with one random column of $J$ resulting ...
New_student's user avatar
2 votes
1 answer
3k views

Frequency Domain Interpolation: Convolution with Sinc Function

I am reading the paper, Design of an energy-efficient accelerator for training of convolutional neural networks using frequency-domain computation, and I came across the following definition of sinc ...
Eduardo Reis's user avatar
3 votes
1 answer
166 views

Machine learning for denoising MRI images

I'm currently a sophomore in college and pretty new to the field of research. I'm currently working on an existing algorithm for MRI de-noising and the results are nothing that great. I can't see how ...
anonymous2718's user avatar
5 votes
4 answers
8k views

Apply Principal Component Analysis (PCA) for RGB Images

I've implemented a method to compute PCA on grayscale images. I haven't seen PCA on RGB images yet, which left me wondering if it is possible to perform it. With RGB images, is PCA done for each ...
Jorge's user avatar
  • 51
1 vote
1 answer
159 views

Can CV or DS be seriously considered DSP roles? [closed]

This is not a technical question but can have a yes/no answer, and a why statement. My understanding about digital signal processing (DSP) is that it allows to take real-world analog signals (1D, 2D, ...
JMFS's user avatar
  • 336
-1 votes
1 answer
85 views

Can Convolution neutral network train(learn) separately (train different times)?

I am new in Convolution neutral network(CNN). My question is, is there a way to let CNN train separately? For example, at very beginning, CNN only need to learning hardwriting 0 and 1. After the ...
Sunson29's user avatar
0 votes
1 answer
103 views

Is it possible to use k-means algorithm with just one vector

Suppose I have a vector $X = (x_1, x_2 , . . . ,x_n)$, $x_i$ is the maximum of $X$ and $x_k$ is the minimum. Is it possible to use k-means algorithm to cluster the values in vector $X$ into two ...
New_student's user avatar
1 vote
0 answers
103 views

Continuous-time RNN and Shannon sampling theorem

The most-used discrete-time RNN equations used in Deep Learning these days are those of Elman: I have seen two very different continuous-time version of these, with different justifications. The most ...
samlaf's user avatar
  • 111
1 vote
0 answers
36 views

How to classify overlapped signals?

A known signal, signal 1 got overlapped with an unknown signal. Likewise, signal 2 overlapped with another unknown signal. The problem I face now is how to classify the overlapped signals based on the ...
user41581's user avatar
0 votes
0 answers
74 views

Detecting similar behaviour in audio files

Can anyone help, I'm trying to find a solution that would allow me the ability to look at a batch of .WAV files and detect ones which share a similar behaviour in the recording like the image attached....
Arron's user avatar
  • 1
0 votes
1 answer
73 views

Generating audio clip by superposing two files

I'm currently trying to generate a set of audio files where some audio events (e.g. dog bark) are immersed in a background audio scene (e.g. crowd noise). I understand that if the event would have ...
fred_101512's user avatar
0 votes
0 answers
40 views

K-Fold Cross-Validation With Only a Low Identification Accuracy for the First Fold

I am using K-Fold cross validation from sklearn.model_selection for evaluating the performance of my model. K=10 and the K-fold cross-validation is set as: ...
I.O Animasahun's user avatar
1 vote
1 answer
580 views

Generate audio data using VAE+GAN

I am trying to train a VAE+GAN model to generate sounds produced by honeybees. I build my model by slightly modifying this tutorial, which aims to generate new MNIST images. Since my data are 1D ...
Steven Chan's user avatar
0 votes
0 answers
88 views

Peak Analysis vs Machine Learning

I am unsure about which approach is "better" (less time good accuracy) for classifying gestures: The system is a doppler radar that returns I and Q signals Approach 1: Have several subject perform ...
wwjdm's user avatar
  • 179
1 vote
0 answers
230 views

audio sound localization using machine learning [closed]

I'm trying to localize a sound by using an array of microphones, the localization is done based on the sum and delay algorithm. I'm trying to to do the same in machine learning. I don't have much ...
Alwyn's user avatar
  • 11
1 vote
0 answers
1k views

How to overcome different MFCC coefficients distributions from different speech datasets?

I am using MFCC values as features for a machine learning model of speech, detecting age from a voice recording of a person. I work with voice datasets I found on the web: common-voice and vctk. ...
Shiran's user avatar
  • 11
2 votes
2 answers
940 views

Converting speech audio to telephone audio

I am trying to train a machine learning algorithm on telephony speech audio. However, there isn't really enough data for this anywhere that I can find. My solution is to just use speech audio from ...
Harry Stuart's user avatar
1 vote
1 answer
267 views

Techniques to reject noisy neural network input

Suppose an artificial neural network is used to approximate a sine wave (shown in red in the graph below), given the linear input variable $x$ (scaled such that the ANN input is $x_{\rm nn}\in[-1;1]$)....
aslan's user avatar
  • 165
0 votes
1 answer
43 views

Conversion of airflow signal into 1-D as a input for CNN [closed]

Trying to detect apnea from airflow signal. I have 100 files of the patient each file contains at least 8 hours of data and sampling rate is 32 Hz. How to prepare my dataset which is used as an input ...
Alok Mishra's user avatar
1 vote
0 answers
2k views

Cocktail Party Problem — audio source separation

I am trying to solve the Cocktail Party Problem. I am trying to separate these two mixed audio files: mixed 1 [WAV] mixed 2 [WAV] into 2 separate audio files that contain the 2 original sources, ...
keke's user avatar
  • 19
4 votes
1 answer
4k views

Is there a penis-detection demo similar to face-detection?

Is there a script/tutorial/demo for penis-detection similar to this one on face-detection? This is a fairly serious question, as the future of Internet memes is at stake. Breast / nipple detection ...
Mars Robertson's user avatar
2 votes
1 answer
5k views

Formula to calculate Cepstral coefficients (not MFCC)

I am currently working with non-audio signals of which I would like to calculate the Cepstrum coefficients with Python so that I can use them with machine learning algorithms. That's probably a quite ...
Frank's user avatar
  • 21
6 votes
1 answer
7k views

Python: Least Squares Support Vector Machine (LS-SVM)

I'm looking for a Python package for a LS-SVM or a way to tune a normal SVM from scikit-learn to a Least-Squares Support Vector Machine for a classification problem. The goal of a SVM is to maximize ...
phappy's user avatar
  • 71
2 votes
1 answer
638 views

MFCC Classification

I'm working on gender estimation from speech signal and I completed MFCC feature extraction. So now I'm trying to estimate gender from these features. But I have frames for an audio file and I ...
Sertaç Bazancir's user avatar
0 votes
1 answer
542 views

Outlier Detection after Detrending a Time Series With Missing Values or NaN

Goal Substitute outliers in a time series by most recent valid data Problem The time series (end-of-day stock prices) has several 'uncomfortable' properties: It is non-stationary and can have ...
ascripter's user avatar
  • 101
5 votes
1 answer
3k views

Downsampling audio for use in Machine Learning

I'm trying to use the work (Neural Networks) done in this repo: https://github.com/jtkim-kaist/VAD It says this: Note: To apply this toolkit to other speech data, the speech data should be ...
Finn Maunsell's user avatar
-3 votes
2 answers
795 views

sound classification

Hello I am trying to do sound classification in matlab. I have different samples of sounds for 2 seconds. How can I proceed with that. The sounds I am using are churchbell, footsteps, trains, sirens ...
Aaly's user avatar
  • 1
-1 votes
3 answers
461 views

Features Used for Instrument Recognition?

I'm building a neural network for instrument recognition based on the IRMAS data set. However, I'm a bit at a loss for what features to use. MFCC seems to be quite popular but extracting this per ...
neverreally's user avatar
2 votes
1 answer
79 views

How to correctly classify voice from other sound events?

I have a huge labeled dataset of several thousand sound events, including human voice, dish washing, things falling to the ground, among others. I need to report when a human voice event takes place....
felipeduque's user avatar
1 vote
1 answer
3k views

Feature Extraction of FFT for One Class SVM

I'm looking for a good way of extracting features from the frequency domain of vibration data for a one-class support vector machine. The image below shows an example from the dataset found in this ...
VegardKT's user avatar
  • 113
3 votes
2 answers
137 views

How can I take a fixed number of bins after N-point DFT when N is unknown?

I am working with machine learning for time series classification. I am trying to extract features from the amplitude spectrum. My current concern is that I cannot tell the length of the signal in ...
ishouldknowtheanswerbutidont's user avatar
1 vote
0 answers
113 views

Why prediction by AR model causes time lag

Why does prediction by AR model cause a time lag? Please tell me why theoretically.
Tatuya Hoshi's user avatar
3 votes
1 answer
298 views

What is a segmentation mask in the paper "Fast Edge Detection Using Structured Forests"

I've read the paper about edge detection, in this paper they treat edge detection as a learning problem which takes an image patch as input and output a label, a binary edge map or a segmentation mask,...
LtChang's user avatar
  • 31
1 vote
1 answer
99 views

Images similarity measure using Jeffrey’s Divergence (j Divergence)

I need to reproduce the result of Xu, Xiaocong, et al, 2016 paper . Mutual information code already was done and work fine. Can anyone help me to write Jeffrey’s divergence code? Because the I use ...
Mohammad nagdawi's user avatar
0 votes
2 answers
381 views

How should someone start to learn machine learning and computer vision for mobile applications? [closed]

I am very interested in learning Machine Learning and Computer Vision for mobile apps, for iOS and Android. But I have no clue or even a slight idea on how to even begin. I know this is heavy on math ...
Boklee's user avatar
  • 3
0 votes
1 answer
471 views

How to predict next image in a sequence, or predict the deblurring of an image?

I have 3 versions of an image at lower resolutions - 480p, 720p, and 1080p. Is it possible to use those 3 images to predict the next highest resolution image (the 4k image)? My first guess was that ...
TooHungryForThis's user avatar
1 vote
2 answers
113 views

What is the type of these signals?

I want to do some DSP and Machine learning experiments on Electrical and Acoustic signals, but, due to some language setbacks, I didn't know how to call the type of my signal, what I use to google now,...
Zakorakis's user avatar
4 votes
3 answers
212 views

Classifing audio signals to detect fault

The basic idea i'm working on is automatic fault detection using audio signals captured from Motor. I have like set of sample audio signal which are recorded when there is no fault and with fault at ...
prabhakar-sivanesan's user avatar
0 votes
1 answer
190 views

How to obtain the probability of a detection?

I will use a specific example from image processing to illustrate my question, but I'm actually interested in the higher level / abstract procedure. I must lack the specific vocabulary and my hunch is ...
KooDooMoo's user avatar
  • 101
1 vote
0 answers
266 views

How to use frame based audio features for machine learning

I have an audio recording (wav file) that is 2 seconds long. That is my sample and it needs to be classified as [class_A] or [class_B]. To extract MFCC features, I divided the sample into frames (183 ...
Learthgz's user avatar
  • 132
5 votes
1 answer
127 views

Compression Sensing for Blind Source Separation

I am new to Signal Processing, and am interested in compression sensing for audio files. CS is based on the algorithm that, given some sampling of a signal $f$ in order to obtain a smaller (compressed)...
Yada Pruksachatkun's user avatar
2 votes
1 answer
107 views

Neural Networks for rotated character (or shape) recognition

I have built a program that recognizes shapes and characters, using Neural Networks. Now, one of the main requirements of the task is that the program can recognize them regardless of rotation or ...
KansaiRobot's user avatar
0 votes
0 answers
170 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 ...
Dov's user avatar
  • 265
1 vote
0 answers
107 views

Classify Different Video Frames by the Effect

I'm trying to do shot boundary detection using SVM's. I'm differentiating between 3 shots, cut, fade and dissolve + (normal frames). I had used two features, shannon's entropy and variance, it gave ...
astroman's user avatar
0 votes
1 answer
347 views

How to use Principal component Analysis(PCA) to extract feature from images [closed]

How can use principal component Analysis to extract feature from image that is been acquired by the camera?
Bakare's user avatar
  • 11
-1 votes
1 answer
197 views

Want to do shot boundary detection via SVM, what are some good features?

I want to do shot boundary detection via SVM's. I'm dividing the frame into nxn blocks. Per block I'm finding these features: shannons entropy edges (H,V,Diag) standard deviation for consecutive ...
user26763's user avatar
1 vote
2 answers
399 views

Need of $\tt abs()$ method when plotting a power spectral density for a given dataset

I am a newbie in signal processing and would like to know the significance of using the abs() function and squaring the values received as an output of ...
Jalaj Maheshwari's user avatar