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Signal and Image Analysis for Biomedical and Life Sciences

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Cover of 'Signal and Image Analysis for Biomedical and Life Sciences'

Table of Contents

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    Book Overview
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    Chapter 1 Visual Analytics of Signalling Pathways Using Time Profiles
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    Chapter 2 Modeling of testosterone regulation by pulse-modulated feedback.
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    Chapter 3 Hybrid Algorithms for Multiple Change-Point Detection in Biological Sequences
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    Chapter 4 Stochastic anomaly detection in eye-tracking data for quantification of motor symptoms in Parkinson's disease.
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    Chapter 5 Identification of the Reichardt Elementary Motion Detector Model
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    Chapter 6 Multi-complexity Ensemble Measures for Gait Time Series Analysis: Application to Diagnostics, Monitoring and Biometrics.
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    Chapter 7 Development of a motion capturing and load analyzing system for caregivers aiding a patient to sit up in bed.
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    Chapter 8 Classifying Epileptic EEG Signals with Delay Permutation Entropy and Multi-scale K-Means.
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    Chapter 9 Tracking of EEG Activity Using Motion Estimation to Understand Brain Wiring.
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    Chapter 10 Towards Automated Quantitative Vasculature Understanding via Ultra High-Resolution Imagery.
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    Chapter 11 Cloud based toolbox for image analysis, processing and reconstruction tasks.
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    Chapter 12 Pollen image classification using the classifynder system: algorithm comparison and a case study on new zealand honey.
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    Chapter 13 Digital image processing and analysis for activated sludge wastewater treatment.
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    Chapter 14 A Complete System for 3D Reconstruction of Roots for Phenotypic Analysis
Attention for Chapter 13: Digital image processing and analysis for activated sludge wastewater treatment.
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Citations

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Chapter title
Digital image processing and analysis for activated sludge wastewater treatment.
Chapter number 13
Book title
Signal and Image Analysis for Biomedical and Life Sciences
Published in
Advances in experimental medicine and biology, October 2014
DOI 10.1007/978-3-319-10984-8_13
Pubmed ID
Book ISBNs
978-3-31-910983-1, 978-3-31-910984-8
Authors

Muhammad Burhan Khan, Xue Yong Lee, Humaira Nisar, Choon Aun Ng, Kim Ho Yeap, Aamir Saeed Malik

Editors

Changming Sun, Tomasz Bednarz, Tuan D. Pham, Pascal Vallotton, Dadong Wang

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 17%
Lecturer 5 8%
Researcher 4 7%
Professor > Associate Professor 4 7%
Student > Doctoral Student 2 3%
Other 6 10%
Unknown 28 47%
Readers by discipline Count As %
Engineering 13 22%
Environmental Science 3 5%
Chemical Engineering 2 3%
Computer Science 2 3%
Unspecified 1 2%
Other 4 7%
Unknown 34 58%