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Articulated Motion and Deformable Objects

Overview of attention for book
Articulated Motion and Deformable Objects
Springer International Publishing

Table of Contents

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    Book Overview
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    Chapter 1 Mammographic Mass Segmentation Using Fuzzy C–means and Decision Trees
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    Chapter 2 Refining the Pose: Training and Use of Deep Recurrent Autoencoders for Improving Human Pose Estimation
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    Chapter 3 How Can Deep Neural Networks Be Generated Efficiently for Devices with Limited Resources?
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    Chapter 4 Controlling a Smartphone with Brain-Computer Interfaces: A Preliminary Study
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    Chapter 5 Capturing Industrial Machinery into Virtual Reality
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    Chapter 6 Leishmaniasis Parasite Segmentation and Classification Using Deep Learning
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    Chapter 7 Robust Pedestrian Detection for Semi-automatic Construction of a Crowded Person Re-Identification Dataset
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    Chapter 8 Shape and Appearance Based Sequenced Convnets to Detect Real-Time Face Attributes on Mobile Devices
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    Chapter 9 Image Colorization Using Generative Adversarial Networks
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    Chapter 10 Multimodal Deep Learning for Advanced Driving Systems
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    Chapter 11 Optical Recognition of Numerical Characters in Digital Images of Glucometers
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    Chapter 12 A Comparison of Text String Similarity Algorithms for POI Name Harmonisation
Attention for Chapter 4: Controlling a Smartphone with Brain-Computer Interfaces: A Preliminary Study
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Citations

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13 Mendeley
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Chapter title
Controlling a Smartphone with Brain-Computer Interfaces: A Preliminary Study
Chapter number 4
Book title
Articulated Motion and Deformable Objects
Published by
Springer, Cham, July 2018
DOI 10.1007/978-3-319-94544-6_4
Book ISBNs
978-3-31-994543-9, 978-3-31-994544-6
Authors

Víctor Martínez-Cagigal, Eduardo Santamaría-Vázquez, Roberto Hornero, Martínez-Cagigal, Víctor, Santamaría-Vázquez, Eduardo, Hornero, Roberto

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 23%
Other 2 15%
Student > Master 2 15%
Researcher 1 8%
Professor > Associate Professor 1 8%
Other 0 0%
Unknown 4 31%
Readers by discipline Count As %
Computer Science 3 23%
Engineering 2 15%
Neuroscience 1 8%
Unknown 7 54%

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