Questions tagged [deep-learning]
The deep-learning tag has no usage guidance.
66
questions
0
votes
1answer
37 views
When a face collapses into a swirling black hole on a video conference call like this is it due to some advanced AI-based error-correction gone wrong?
Within this newscast video1 a video conference call is shown. Between 02:23 and 02:37 the face of the interviewee appears to get ...
4
votes
3answers
128 views
Role of window length and overlap in uncertainty principle?
I am trying to predict epilepsy using spectrograms and a convolutional neural network.
So far I have achieved a validation accuracy of 86% which i feel like is pretty good. Lots of the papers doing ...
1
vote
1answer
29 views
How to train a FCNN with Spectrogram images?
I'm working on a audio dereverberation deep learning model, based on the U-net architecture.
The idea of my project came from image denoising with autoencoders. I feed the reverbered spectrogram to ...
5
votes
1answer
72 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?
0
votes
0answers
20 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 ...
1
vote
2answers
57 views
How to choose a deep learning model?
I have split the database available into 70% training, 15% validation, and 15% test. I have trained the model and got the following results:
training accuracy 100%, validation accuracy 97.61%, test ...
4
votes
1answer
77 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-...
4
votes
2answers
58 views
When to Use Composite Filters and When to Use Separable Filters?
I’m a beginner in image processing, and was wondering since seperated (decomposed) filters help give faster and more efficient results, when do we even need to use composite filters? All I heard is ...
5
votes
2answers
131 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 ...
0
votes
0answers
37 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 ...
0
votes
0answers
21 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 ...
1
vote
0answers
66 views
Can we use AutoEncoder for Sparse Sensing?
Is there a way to introduce sparsity constraint on an autoencoder to achieve compressions in the Cosine/Fourier domain? I want to use the encoder part of the Auto encoder as the feature extractor from ...
0
votes
1answer
34 views
Classification of very noisy EMG signals
I'm an absolutely newbie to signal processing. I'm trying to classify EMG signals which are very noisy (decibel values are more than -70 dB in some cases). After applying EMD technique these values ...
4
votes
1answer
60 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 ...
4
votes
1answer
53 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,...
0
votes
1answer
34 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?
0
votes
0answers
43 views
pre-trained deep residual networks based on transfer learning
According to the following paper:
Deep Residual Learning for Image Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun; Proceedings of the IEEE Conference on Computer Vision and Pattern ...
1
vote
0answers
19 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. ...
0
votes
0answers
9 views
FPR for time series of 1 hour epilepsy recording
I am working on epilepsy seizure prediction classification using a convolution neural network. My dataset consisting of multiple recording of each record for 1 hour, first I segmented each record into ...
0
votes
0answers
9 views
Upsampling class activation maps for discriminative feature localisation
I am currently reading a paper by on learning deep features for discriminative localization where the authors propose to use class activation maps to learn discriminative localised features. The ...
0
votes
0answers
15 views
Use of spectrograms in using deep learning on EEG related problems
I am currently working on a classification problem related to EEG signals. My professor asked me to convert those signals into their spectrograms and try various convolutional neural networks on them. ...
0
votes
0answers
51 views
Deep Learning for Online EEG Denoising
I'm currently working on the development of deep learning methods for online artifact removal from EEG signals. I'm interested in removing common biological artifacts such as EOG and EMG individually ...
0
votes
0answers
38 views
Audio RMS normalization prior to a DNN classification
I want to normalize my data prior to a deep neural network model (DNN). It was recommended to me to use real mean square (RMS) normalization for audio, though I am not sure this is the best for a DNN. ...
3
votes
1answer
114 views
how to handle different durations of audio data?
I am new to signal preprocessing, I read about mel_spectrograms, MFCC's. Now I want to apply it and use the CNN model, But the data which I have for practice is having audio of different durations, ...
0
votes
0answers
29 views
multi-frame image restoration
Suppose we have a sequence of still images each of which has been contaminated by some particles(ex, dust/sand/smoke) making the images very poor in certain areas.
What approach would be best to teach ...
5
votes
2answers
356 views
Classic Signal Processing vs Deep Learning / Machine Learning (DNN / ML) Based Signal Processing
Are classic signal processing/statistics based approaches to optimum detection/estimation still relevant/important compared to ML based approaches using DL?
There was a time when speech processing was ...
1
vote
1answer
34 views
Why not use synthetic datasets for training machine vision (deep learning) algorithms?
I am studying some examples of how to perform 3D instance segmentation in indoor scenes, and I have noticed many of the available datasets are from real environments. I was wondering with the ...
1
vote
0answers
28 views
what should be a good bibliography for deep learning in 2020
What should be a good bibliography for having a good overview of deep learning (on image/signal processing) in 2020 ?
0
votes
0answers
47 views
Remove noise from VGA image
I have 2 color images generated from same X-ray machines, but one of the image is obtained using VGA cable. Therefore the RGB intensities differ in the 2 images. I am using Object detection to detect ...
0
votes
0answers
71 views
PCA with CNN Tensorflow
I need to improve my model of Convolutional Neural Network (CNN). The goal is to recognize facial expression.
I've been using some strategies like dropout for regularization and Adam optimazer, but i ...
0
votes
1answer
59 views
How to prepare different input size in CNN
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 ...
0
votes
1answer
63 views
Deep Learning: Classification vs. Convolution for Signal Restoration
Assume we have vector $X = [x_1, x_2, x_3, x_4 ,..... x_N], ∈ -1,1$. Therefore the value of $x$ is either 1 or -1. The vector $X$ is convoluted with random generated vector $Y$ whose length is the ...
0
votes
0answers
29 views
Audio in Image,Graph or WaveForm Representation
Our task is to feed the audio data into the deep learning tensor flow model in the form of image representation(or graphical,waveform). Question is what is the best way of representing audio in image ...
0
votes
0answers
587 views
Understanding liftering as the final step in MFCCs features extraction
In the book here, they apply liftering, as a final step of MFCCs features extraction, to isolate the system component by multiplying the whole cepstrum by a rectangular window centred on lower ...
1
vote
0answers
33 views
Adversarial training: deep learning book
In the Deep Learning book of Ian Goodfellow, p. 261 it is shown how to build an "adversarial example" by adding to an image $x$ another image $x_{adversarial}$ build as epsilon times and image (same ...
0
votes
0answers
50 views
Deep Learning based NDA Channel Estimation
I was wondering if it is possible to use Deep Learning to estimate the Channel Impulse Response for NDA synchronization?
I understand Deep Learning is not normally used for regression problems but I ...
1
vote
2answers
82 views
Could modulation/coding schemes be generated from an AI?
Warning: I'm a bit of a noob with respect to this entire field, but I took some classes on it (a few years ago) and found it fascinating.
Anyhow, as far as I understand it, modulation is the process ...
0
votes
1answer
33 views
Removing vocal but retaining all background ambient noises
I have one audio file containing human speeches, a lot of ambient noises like audience laughter, birds chirping, sounds of natures etc..
Now I want to separate it into two audio files where one ...
1
vote
1answer
71 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-...
0
votes
0answers
40 views
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 ...
1
vote
1answer
65 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 ...
2
votes
1answer
2k 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 ...
1
vote
1answer
57 views
Are delta and double delta features needed when classifying with LSTM
I understand that the combination of MFCCs, deltas and double deltas is a good feature to be used with HMMs for keyword detection problems. HMMs are limited by Markov Property and this limitation is ...
3
votes
1answer
230 views
Augmentation for EEG signal classification using Deep Learning
Augmentation is a technique that we use in deep learning for expanding the training dataset. It includes different ways of modifying an image and adding it to the training dataset. My question is if ...
1
vote
1answer
505 views
How to express STFT and ISTFT as a 1d convolution and 1d deconvolution in tensorflow/keras
I'm trying to implement this paper in tensorflow and keras. At the end of section 3 it says.
...
2
votes
2answers
1k views
audio spectrogram normalization
I am performing language classification from audio signals using mel-spectrograms as my inputs for a ResNet. It works well as long as all of my audio data from different languages is from the same ...
4
votes
1answer
338 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 ...
0
votes
1answer
63 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 ...
1
vote
2answers
837 views
What fps can be considered as a hardline for real-time performance? Is there any academic paper that describes this?
I am trying to design a deep learning based inferencing solution for security applications. My deployed program achieves an FPS of 15fps for classification. Can it be considered real-time?
6
votes
3answers
3k 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 ...
