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No prior research? What am I not understanding? Using deep learning to enhance videos by predicting the best filters or histogram transforms to apply

I would like to make a large set of videos more visually pleasing by adjusting colors, saturation, contrast, etc. However, the techniques that I can find online roughly fall into these two categories: ...
elgehelge's user avatar
  • 111
2 votes
1 answer
48 views

2d convolution: What is the difference between convolution using blocked Toeplitz matrix and convolution layers?

For a given matrices $A$ of size $4\times 4$ and $B$ of size $3\times 3$ then I construct a blocked Toeplitz matrix and perform the convolution. The resulting output is of size $6 \times 6$. I have no ...
jomegaA's user avatar
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81 views

Processing of Channel State Information from WiFi for Generalizability

For my master's thesis I collected CSI with 4 WiFi network cards (Intel AX210) for three different persons for 102 positions (spaced roughly 30cm apart). The covered area was around 10m x 7m and in ...
binaryBigInt's user avatar
1 vote
1 answer
80 views

Tapped delay line + ADALINE = Adaptive filter?

When studying neural networks from Neural Networks and Learning Machines, by Simon Haykin, the author highlights the close similarity between of adaptive filtering and neural networks. From a scalar-...
Rubem Pacelli'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
4 votes
1 answer
152 views

Understanding an adaptative single neuron PID controller

I only know the "vanilla" use of a Kalman filter and I am currently trying to understand an article available here (the algorithm is presented in the 6 first pages) : Adaptive Single Neuron ...
NokiYola's user avatar
  • 507
1 vote
0 answers
126 views

State-of-the-art non-training based stereo matching algorithm

In the world of 3D vision, constructing a 3D model from multiple view imagery is an important topic. The stereo matching step is one of the most crucial steps. Based on the benchmark of KITTI2012 and ...
Lion Lai's user avatar
  • 213
1 vote
1 answer
237 views

Log of Filterbank Energies

In common literature, when generating spectrograms, mel-spectrograms, and cochleagrams, the log of the resulting filterbank energies is taken. Why is this done? I notice that my convolutional neural ...
Lyle's user avatar
  • 11
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0 answers
22 views

Question about "A neural algorithm of artistic style"

My question is based on the paper. This paper introduced a loss function by calculating two-loss: the loss between the white noise input and style image and the loss between the white noise input and ...
sss's user avatar
  • 23
0 votes
1 answer
314 views

How to convert depth to disparity

if $k = \text{baseline}\cdot\text{focal length}$ is known, then the disparity is the ratio of $k$ to depth $d_\text{image}$: $$D_\text{image} = \frac{k}{d_\text{image}}$$ I have a ...
Oscar L's user avatar
  • 19
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1 answer
800 views

normalize STFT output by magnitude

I am using torch.stft() to generate spectrograms for neural networks and come across the below code. ...
JXuan's user avatar
  • 55
3 votes
2 answers
375 views

Optimize window length (STFT) via gradient descent (in neural networks)

The authors from this paper optimized a Gaussian window size via gradient descent (the σ parameter of the bell curve) together with the other parameters of neural networks. I don't use Gaussian window ...
JXuan's user avatar
  • 55
0 votes
0 answers
28 views

How can I speech enhancement with DNN?

I want to do speech enhancement with DNN on Matlab. I downloaded the TIMIT dataset from the internet as a .wav file. I also downloaded the noises from the Noisex-92 database as .m file. Now I need to ...
Zang Li's user avatar
  • 59
2 votes
2 answers
815 views

Is a neural network an adaptive filter?

I am confused as to the difference between neural networks and adaptive filters: As far as I understand it, "neural networks" are largely used for solving inverse problems, where an unknown ...
Bulbasaur's user avatar
  • 209
5 votes
2 answers
546 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
4 votes
1 answer
304 views

Perform Transposed Convolution in Spectral / Frequency Domain?

I'm doing some experimentation on performing end to end generative modeling in the frequency domain. I've got a working convolutional layer, but do not yet have a Conv2DTranspose equivalent. Please ...
Luke Wood's user avatar
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
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0 votes
1 answer
29 views

Training a NN classifier on a single\double channel out of a surround sound dataset

I want to train a neural network for a classification task on the VSD2014 dataset. I have downloaded the movies, but they have a 6 channel audio format (surround sound). 6 channels will cost a very ...
havakok's user avatar
  • 682
1 vote
1 answer
827 views

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 ...
moinudin's user avatar
  • 141
0 votes
0 answers
77 views

Filter Bank and Auto-Encoder

I'm trying to find an intuition behind auto-encoder using an analogy with filter banks. I can comprehend the encoder and analysis filters in a filter bank as extracting features from the input signal ...
tushar's user avatar
  • 101
2 votes
1 answer
633 views

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?
sam's user avatar
  • 21
2 votes
1 answer
6k views

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 ...
Vishal Rana's user avatar
0 votes
0 answers
37 views

How can I find the delay between two signals? [duplicate]

I am using NARX in Matlab. Is there any method to find the delay between input and output signals? My aim is to decrease memory length by finding the delay. TIA.
murat's user avatar
  • 1
0 votes
0 answers
27 views

How can a CNN account for spectro-temporal constraints in neural data?

What are there the best ways to leverage the unique "geometrical" constraints of spectro-temporal signal representations (architecture, filter shapes, data augmentation, etc.)? For example, ...
bez's user avatar
  • 1
1 vote
1 answer
43 views

FFT question as it relates to Neural Networks / Supervised Learning Models

So I've been researching wavelet transforms and FFT. I want to feed wavelet transforms of a 1D signal in time into a neural net and train against a target variable at each time step. The idea being ...
Tyler Gaye's user avatar
1 vote
1 answer
347 views

How to train and test deep neural network using MFCC features?

I am working on Voice Disorder Detection problem. I have extracted 13 MFCC features, 13 delta and 13 delta-delta features from each audio file (2 to 4 secs). I extracted these features for each frame (...
Irfan Ansari's user avatar
3 votes
2 answers
170 views

How to Design a Model based on Convolutional Neural Network (CNN) which Supports Arbitrary Input Size in Training and Production

I'm doing a research about personality identification based on their signature using CNN method, however the learning feature for the personality traits have a different input size. I understand that ...
Smurf Again's user avatar
0 votes
0 answers
27 views

Functioning of a continuous data stream processing neural network?

I've been searching with unfortunately no relevant results about something I have trouble to figure out: neural networks which process continuous data stream (audio, video, anything with a state ...
CodeTalker's user avatar
-1 votes
1 answer
506 views

STFT to spectrogram

I would like to know whether I am correct in my understanding of going from STFT to a spectrogram. My goal is to convert a spectrogram back to a wav file. If I have my STFT: ...
Harry Stuart's user avatar
1 vote
2 answers
117 views

Neural networks in system identification - What type of activation functions?

I made a free software for all operative systems, even Android. It's called Deeplearning2C. It can train a neural network and generate C code and MATLAB-code. C-code for embedded systems and MATLAB-...
euraad's user avatar
  • 405
0 votes
0 answers
112 views

Using unlabeled EEG data for Machine Learning

I am working on a project that is basically a game for motor-paralyzed people. It should take an EEG signal from FP1 channel of brain and then after processing it should generate command for the game ...
majid bhatti's user avatar
2 votes
1 answer
130 views

Deriving the Langrangian interpolation polynomials in Cook-Toom convolutions

I'm working through Blahut's 'Fast Algorithms for Signal Processing'. Trying to develop an intuition for the Cook-Toom algorithm for convolutions as used by Lavin and Gray in their Winograd paper for ...
Daniel Soutar's user avatar
1 vote
1 answer
73 views

Develop a simple image classification system by using Laplacian of Gaussian (LoG)

I am tring to write a simple CAD system to classify some images within two groups by using Laplacian of Gaussian (LoG). I am using scikit-image for this tasks and I want to use DNN in keras to train a ...
Allianz1's user avatar
-1 votes
1 answer
84 views

Reconstruct images from PCA reduced dimensions with NN

I was reading this Medium post and I had the idea to reconstruct the original images with a convolutional neural network instead of applying the inverse transform method. The problem is that I don't ...
Jorge's user avatar
  • 51
0 votes
0 answers
27 views

What features can I extract from optical fibre signal?

I have sensors placed in pipelines and I have amplitudes coming from it. I want to detect the type of activity taking place at the sensors(like digging,tunneling,clamping etc). So I have a signal ...
Fasty's user avatar
  • 101
0 votes
0 answers
454 views

Upsampling and downsampling signals as a preprocessing step for a neural network

I have audio data acquired from a 4 channels sensors array. As a preprocessing step for a neural network, I want to beamform and focus on the sound source. For higher resolution in the beamforming ...
havakok's user avatar
  • 682
5 votes
4 answers
369 views

After advice about detecting focus quality of objects in a photo detected using YoloV3

I've spent the last couple of days playing with YoloV3, and have had very good results. My use case is sports photography, and the object detection for people/bikes etc is very very good, I'm very ...
Codemonkey's user avatar
4 votes
1 answer
920 views

How to Remove the Patch Artifacts of Neural Network Denoising Process?

I have written a python script which uses the Noise2Noise: Learning Image Restoration without Clean Data implementation of the Auto Encoder which is useful to remove noise from images. In the original ...
Dawid's user avatar
  • 165
0 votes
1 answer
119 views

What does it mean for a Wavelet transform to commute with translations?

Referencing this article here https://arxiv.org/pdf/1203.1513.pdf It states "A wavelet transform commutes with translations, and is therefore not translation invariant". Now I understand why it is a ...
Izzo's user avatar
  • 882
1 vote
0 answers
115 views

Image from Inverse FFT operation is sparse

I'm trying to train a deep nerual network that takes in input, an signal in the frequency domain, and attempts to learn a mapping to another signal in the frequency domain. Basically, the input to ...
Reptilian'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
860 views

Recover Audio from Spectrogram Image

I have applied transformation(Constant Q Transformation) to my audio time domain signal, this gives me Frequency vs Time representation. Now, the CQT values consists of complex values(84*260), but ...
Krish's user avatar
  • 101
2 votes
1 answer
2k views

What is the best input for de-noising autoencoder for sound data?

I am currently trying to build an autoencoder to de-noise audio data. However I have not found any good articles explaining about the input to the autoencoder, i.e. feature vector. As in speech ...
Wave's user avatar
  • 21
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
297 views

Generalized translation on graph

David I.Shuman in "vertex-frequency analysis on graph" claims that,"we generalize one of the most important signal processing tools – windowed Fourier analysis – to the graph setting and When we apply ...
niloofar jamshidi's user avatar
7 votes
1 answer
717 views

"Bi Directional" Kalman Filter - Kalman Filter for Smoothing

I am working on a project in Object Tracking, i.e. need to predict the location of next bounding box. I used a Hungarian algorithm with a Kalman Filter (which is a common method in this domain) which ...
Anuar Y's user avatar
  • 181
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
1 vote
1 answer
5k views

Convolution and Cross Correlation on 2D Image

I have read that convolution and cross-correlation are the same thing, but convolution flips 180 degrees (images), or time reverses (sequences) the kernel, before performing the elementwise ...
sdiabr's user avatar
  • 209
7 votes
3 answers
4k views

Neural Networks and Complex Valued Inputs

[not sure if this or stats.stackexchange was the correct location for this post, so put it on both for now.] I've seen some recent papers describing complex valued neural networks like this one: Deep ...
Austin's user avatar
  • 281
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