Signal Processing Stack Exchange
Signal Processing Stack Exchange

Questions tagged [deep-learning]

65 questions
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Is deep learning killing image processing/computer vision?

I'm looking forward to enroll in an MSc in Signal and Image processing, or maybe Computer Vision (I have not decided yet), and this question emerged. My concern is, since deep learning doesn't need feature extraction and almost no input…
Tony
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When is a network called end-to-end training?

In machine learning, we often see the expression "end-to-end" learning (or training). However, I do not know that it means. When is a network called end-to-end training? How to recognize a network is end-to-end learning?
user3051460
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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 Complex Networks, 2017, Trabelsi et al.. What I'm…
Austin
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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?
David
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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 Representations for Convolutional Neural…
Eduardo Reis
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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 done using HMM. While not completely unused most…
FourierFlux
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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 based on Faster R-CNN features for Instance Search if we have a test dataset , and we extract all conv features of all images at test dataset called…
H.H
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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 similar deep learning are using an very high…
niklas Munkholm Hjort
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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-made code on this subject? Which one do you…
Zang Li
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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 the advantages of decomposed filters,but what about…
Simon
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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 note this is not deconvolution! Unfortunately,…
Luke Wood
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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, z - random noise, y - target image and G and D…
ans
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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 paper implementation they were using full images…
Dawid
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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/video classification tasks. They surpassed…
chronosynclastic
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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, now because of this, the mel_spectrograms will be…
Ravi Teja
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