# Sampling (signal processing)

## Papers overview

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Review

2017

Review

2017

- ArXiv
- 2017

The aim of this paper1 is to give an overview of domain adaptation and transfer learning with a specific view on visualâ€¦Â (More)

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Review

2017

Review

2017

- ArXiv
- 2017

This paper is a survey and an analysis of different ways of using deep learning to generate musical content. We propose aâ€¦Â (More)

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Review

2017

Review

2017

- AAAI
- 2017

Although semi-supervised variational autoencoder (SemiVAE) works in image classification task, it fails in text classificationâ€¦Â (More)

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Review

2017

Review

2017

- Bioinformatics
- 2017

Motivation
In recent years, molecular species delimitation has become a routine approach for quantifying and classifyingâ€¦Â (More)

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Review

2017

Review

2017

- Information & Software Technology
- 2017

Context: Defect prediction is a very meaningful topic, particularly at change-level. Change-level defect prediction, which isâ€¦Â (More)

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Review

2017

Review

2017

- Domain Adaptation in Computer Vision Applications
- 2017

The aim of this chapter is to give an overview of domain adaptation and transfer learning with a specific view to visualâ€¦Â (More)

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Highly Cited

2010

Highly Cited

2010

- IEEE Journal of Selected Topics in Signalâ€¦
- 2010

Conventional sub-Nyquist sampling methods for analog signals exploit prior information about the spectral support. In this paperâ€¦Â (More)

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Highly Cited

2008

Highly Cited

2008

- IEEE Signal Processing Magazine
- 2008

In this article, the authors present a new approach to building simpler, smaller, and cheaper digital cameras that can operateâ€¦Â (More)

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Highly Cited

2002

Highly Cited

2002

- IEEE Trans. Signal Processing
- 2002

Consider classes of signals that have a finite number of degrees of freedom per unit of time and call this number the rate ofâ€¦Â (More)

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Highly Cited

1997

Highly Cited

1997

- 1997

Fourier analysis is a family of mathematical techniques, all based on decomposing signals into sinusoids. The discrete Fourierâ€¦Â (More)

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