Questions tagged [neural-network]

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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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81 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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49 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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50 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
179 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
73 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 ...
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15 views

Feature Based Methods for Quality Inspection Problem

I am currently working on an image classification problem to classify thermal images (can be interpreted as false-color images) of certain products as with or without defect. From an initial search in ...
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30 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 ...
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20 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, ...
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15 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 ...
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1answer
121 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: ...
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42 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 ...
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1answer
59 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 ...
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1answer
68 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 ...
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16 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 ...
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353 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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658 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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332 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 ...