Questions tagged [neural-network]

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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 ...
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14 views

Find specific feature within an image / Neural Networks

i am working in the field of image processsing and we have a certain problem which is difficult to solve by rules-defined algorithms. Is it possible to teach a certain pattern into a neural network, ...
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3answers
1k views

Principal Component Analysis (PCA) on Convolutional Neural Network (CNN) Features

Please, I have a question regarding PCA and features which are extracted from a convolutional layer. link if we have a test dataset , and we extract all conv features of all images at test dataset ...
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4answers
117 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 ...
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42 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 ...
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81 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 $x_{\rm nn}\in[-1;1]$)....
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1answer
26 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 ...
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1answer
22 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 ...
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1answer
48 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 ...
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25 views

What would be the input data matrix and target data matrix in MATLAB Neural Network Pattern Recognition toolbox?

I am new to Neural Networks and have no prior experience of AI,ML or deep learning. Please help me out. I have data sets of 10 different kind of hand-motions(Gestures) from M1 to M10. Each hand-motion ...
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0answers
100 views

Using Wavelet Transform on a 1D signal while updating the values

I'm working on a NN that uses Wavlet Transformed signals (with different wavelets and levels) and combines them with an additional Statistical Features input (input_4) to provide one step ahead ...
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0answers
36 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 ...
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192 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 ...
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1answer
136 views

identify a specific table in document image

I have some images of answered tests. I am working on recognizing the answers for the multiple choice questions on each test. A example: I think the problem can be separate into two sub-problems: ...
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0answers
101 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 ...
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1answer
114 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 ...
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1answer
96 views

“Bi Directional” Kalman Filter

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 produced decent results. However, lots of ...
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1answer
734 views

Is there a penis detection demo similar to face detection?

Tutorial for face detection: Is there a script / tutorial / demo for penis detection? These guys ran into some issues: Fairly serious question, future of internet memes is at stake. Breast / ...
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2answers
1k 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 ...
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1answer
687 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 ...
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1answer
73 views

Neural Network learning project based on 8 wave signals over 1 second at 1 sample every 10 ms ( hence 100Hz )

I'm currentely trying to train a neural network that can decide wether a pattern produced by the movement of a hand near capacitive sensors is as expected, or random. I have an MPR121 microchip linked ...
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1answer
141 views

Keyword spotting - constant phoneme length

I wish to implement a keyword spotting algorithm (in speech), on the basis of what was published in this article (Apple's Machine Learning Journal). The article describes a neural-network-based ...
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1answer
72 views

In Convolutional Neural Nets, what do convolutions look like?

The early stages of the Convolutional Neural Networks are performing classical convolutions with a certain kernel size on the input image. Is is possible to express in common terms the type of ...
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1answer
261 views

Pattern recognition in time series 4x3000 vector

I have a vector, here is a sample of some data from some heat flow data: I would like to identify features in this image. In the example above I have identified one feature I would like to ...
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1answer
406 views

What would the target matrix to train Neural Network?

I'm new at Artificial Neural Network and I'm using MATLAB developing Facial expression recognition and There are six expressions ; I'm not able to understand about How to create a target matrix? My ...
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1answer
48 views

Generalizing the chain rule

Given the real-valued functions $f_1$ and $f_2$ with $x\in\mathbb{R}$, then $$ \frac{df_2(f_1(x))}{dx} = \frac{df_2(f_1(x))}{d f_1(x)}\frac{df_1(x)}{dx}$$ Is it then the case that if we also have a ...
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2answers
296 views

Neural Network: Spectrogram Dimension

I like to work with a convolutional neural network in combination with a spectrogram as input. Assuming the spectrogram has the dimensions $T\times F$ (time$\times$frequency). Is it more natural to ...
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1answer
46 views

Deep learning model for phone recognition - issues with dimension the model

I seem to have some problems understandind how the model described in this paper has been designed This is what is written about the model dimension.. ...In these experiments we used one ...
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0answers
67 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 ...
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1answer
146 views

How to apply neural network parallelly on each part of image

I have an image which is divided into four equal size square blocks. I want to apply neural network for denoising. Usually, I apply on the whole image. But i was thinking that is it possible to divide ...
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2answers
380 views

Does an equivalent transformation of a signal to a spectrogram image exist in which the phase information is part of the resulting image?

I'm working on a research project where we would like to apply convolutional neural networks to an image representation of a signal. However, it seems that if I would use a spectrogram, I would end up ...
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3answers
386 views

Neural network with much less positive examples

I am developing a medical algorithm working on large amounts of data. However, as in many medical scenarios I have a lot of negative example and only a few positive ones. So any neural network I train ...
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0answers
259 views

Proper way of representing Static, delta, delta delta in a plot

I am currently working on recreating the result of this paper. The paper is about applying cnn in speech recognition, in which cnn is used to for feature extraction, for which a proper way of ...
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1answer
2k views

Spectrograms for neural nets

General Question Given an audio file, say a 16-bit wav, what are some standard methods to preprocess a spectrogram of this wav so that it may be fed into a neural net? Context In Lee et al's 2009 ...
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2answers
7k views

Can deep neural networks achieve real-time video analysis?

Recently, convolutional neural network based, deep architectures (DNN) such as AlexNet and VGGnet have been very successful in image classification challenges (e.g. ImageNet) and action recognition/...
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1answer
53 views

Good Reference Problem to Test Filtering/Estimation Algorithms

I am looking to figure out if a current filter algorithm I have built could be useful for some problems I am looking into at work. It isn't a Kalman filter, but is instead making estimations using a ...
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1answer
82 views

Answering Machine vs. Human — Neural Network Features Selection

I've been tasked with creating an artificial neural network that can classify a telephone call as either answered by a human or an answering machine. My knowledge of audio processing is, mildly put, ...
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0answers
48 views

Feature maps for a Convolutional Neural Network

I hope this is the right place to ask this, so here goes: I am currently trying to implement a convolutional neural network in C++, but since I have no formal education in signal processing, image ...
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0answers
47 views

Pearson correlation of neural responses with it's linear estimation

I am trying to understand the following fact from this article (page 13): How can single neurons predict behaviour Suppose I have a linear estimation of a stimulus: $ \hat{s} = \mathbf{w}^T(\mathbf{r}...
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1answer
377 views

Delay issue in time series prediction

I am having an issue using neural networks to predict time series. Some predicted data fits with the expected data, as bellow: (In black the real time series and in blue the output of my neural ...
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1answer
152 views

Artificial Neural Network Preprocessing in Real-Time Applications

I've come across an issue with my ANN when attempting to port my offline analysis to an online, real-time, application. I currently train my algorithm using an array of input data, number of ...
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1answer
568 views

FPGA vs DSP for MAC operations

I'm new to SP Stack Exchange . I am doing a project on implementing a handwriting recognition machine using Neural Networks in Real Time . The Image Processing Part involves convolving a 4*5 kernel ...