國立虎尾科技大學 |

Machine intelligence and signal processing

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine intelligence and signal processing/ edited by Richa Singh ... [et al.].
other author:	Singh, Richa.
Published:	New Delhi :Springer India : : 2016.,
Description:	x, 163 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Machine learning. -
Online resource:	http://dx.doi.org/10.1007/978-81-322-2625-3
ISBN:	9788132226253

Machine intelligence and signal processing
Machine intelligence and signal processing[electronic resource] /edited by Richa Singh ... [et al.]. - New Delhi :Springer India :2016. - x, 163 p. :ill., digital ;24 cm. - Advances in intelligent systems and computing,v.3902194-5357 ;. - Advances in intelligent systems and computing ;173..

Chapter 1. Advancing Cross-spectral Iris Recognition Research using Bi-spectral Imaging -- Chapter 2. Fast 3D Salient Region Detection in Medical Images using GPUs -- Chapter 3. Recovering Partially Sampled EEG Signals using Learned Dictionaries -- Chapter 4. Greedy Algorithms for Non-linear Sparse Recovery -- Chapter 5. Improving Rating Predictions by Baseline Estimation and Single Pass Low-rank Approximation -- Chapter 6. Reducing Inter-scanner Variability in Multi-site fMRI Activations using Correction Functions: A Preliminary Study -- Chapter 7. Genetically Modified Logistic Regression with Radial Basis Function for Robust Software Effort Prediction -- Chapter 8. Missing Data Interpolation using Compressive Sensing: An Application for Sales Data Gathering -- Chapter 9. Retinal Vessel Classification based on Maximization of Squared-loss Mutual Information -- Chapter 10. Retinal Blood Vessel Extraction and Optic Disc Removal using Curvelet Transform and Morphological Operation -- Chapter 11. Adaptive Skin Color Model to Improve Video Face Detection -- Chapter 12. Automated Spam Detection in Short Text Messages -- Chapter 13. Domain Adaptation for Face Detection -- Chapter 14. Comparative Study of Pre-processing and Classification Methods in Character Recognition of Natural Scene Images.

This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning - instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning) And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intelligence and Signal Processing was one of the few unique events that are focused on the convergence of the two fields. The book is comprised of chapters based on the top presentations at the workshop. This book has three chapters on various topics of biometrics - two are on face detection and one on iris recognition; all from top researchers in their field. There are four chapters on different biomedical signal / image processing problems. Two of these are on retinal vessel classification and extraction; one on biomedical signal acquisition and the fourth one on region detection. There are three chapters on data analysis - a topic gaining immense popularity in industry and academia. One of these shows a novel use of compressed sensing in missing sales data interpolation. Another chapter is on spam detection and the third one is on simple one-shot movie rating prediction. Four other chapters cover various cutting edge miscellaneous topics on character recognition, software effort prediction, speech recognition and non-linear sparse recovery. The contents of this book will prove useful to researchers, professionals and students in the domains of machine learning and signal processing.

ISBN: 9788132226253

Standard No.: 10.1007/978-81-322-2625-3doiSubjects--Topical Terms:

561253
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Machine intelligence and signal processing
LDR:04539nam a2200325 a 4500 001 860911
003 DE-He213
005 20160722153531.0
006 m d
007 cr nn 008maaau
008 170720s2016 ii s 0 eng d
020 $a 9788132226253 $q (electronic bk.)
020 $a 9788132226246 $q (paper)
024 7 $a 10.1007/978-81-322-2625-3 $2 doi
035 $a 978-81-322-2625-3
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .M149 2016
245 0 0 $a Machine intelligence and signal processing $h [electronic resource] / $c edited by Richa Singh ... [et al.].
260 $a New Delhi : $c 2016. $b Springer India : $b Imprint: Springer,
300 $a x, 163 p. : $b ill., digital ; $c 24 cm.
490 1 $a Advances in intelligent systems and computing, $x 2194-5357 ; $v v.390
505 0 $a Chapter 1. Advancing Cross-spectral Iris Recognition Research using Bi-spectral Imaging -- Chapter 2. Fast 3D Salient Region Detection in Medical Images using GPUs -- Chapter 3. Recovering Partially Sampled EEG Signals using Learned Dictionaries -- Chapter 4. Greedy Algorithms for Non-linear Sparse Recovery -- Chapter 5. Improving Rating Predictions by Baseline Estimation and Single Pass Low-rank Approximation -- Chapter 6. Reducing Inter-scanner Variability in Multi-site fMRI Activations using Correction Functions: A Preliminary Study -- Chapter 7. Genetically Modified Logistic Regression with Radial Basis Function for Robust Software Effort Prediction -- Chapter 8. Missing Data Interpolation using Compressive Sensing: An Application for Sales Data Gathering -- Chapter 9. Retinal Vessel Classification based on Maximization of Squared-loss Mutual Information -- Chapter 10. Retinal Blood Vessel Extraction and Optic Disc Removal using Curvelet Transform and Morphological Operation -- Chapter 11. Adaptive Skin Color Model to Improve Video Face Detection -- Chapter 12. Automated Spam Detection in Short Text Messages -- Chapter 13. Domain Adaptation for Face Detection -- Chapter 14. Comparative Study of Pre-processing and Classification Methods in Character Recognition of Natural Scene Images.
520 $a This book comprises chapters on key problems in machine learning and signal processing arenas. The contents of the book are a result of a 2014 Workshop on Machine Intelligence and Signal Processing held at the Indraprastha Institute of Information Technology. Traditionally, signal processing and machine learning were considered to be separate areas of research. However in recent times the two communities are getting closer. In a very abstract fashion, signal processing is the study of operator design. The contributions of signal processing had been to device operators for restoration, compression, etc. Applied Mathematicians were more interested in operator analysis. Nowadays signal processing research is gravitating towards operator learning - instead of designing operators based on heuristics (for example wavelets), the trend is to learn these operators (for example dictionary learning) And thus, the gap between signal processing and machine learning is fast converging. The 2014 Workshop on Machine Intelligence and Signal Processing was one of the few unique events that are focused on the convergence of the two fields. The book is comprised of chapters based on the top presentations at the workshop. This book has three chapters on various topics of biometrics - two are on face detection and one on iris recognition; all from top researchers in their field. There are four chapters on different biomedical signal / image processing problems. Two of these are on retinal vessel classification and extraction; one on biomedical signal acquisition and the fourth one on region detection. There are three chapters on data analysis - a topic gaining immense popularity in industry and academia. One of these shows a novel use of compressed sensing in missing sales data interpolation. Another chapter is on spam detection and the third one is on simple one-shot movie rating prediction. Four other chapters cover various cutting edge miscellaneous topics on character recognition, software effort prediction, speech recognition and non-linear sparse recovery. The contents of this book will prove useful to researchers, professionals and students in the domains of machine learning and signal processing.
650 0 $a Machine learning. $3 561253
650 0 $a Signal processing. $3 561459
650 1 4 $a Engineering. $3 561152
650 2 4 $a Computational Intelligence. $3 768837
650 2 4 $a Signal, Image and Speech Processing. $3 670837
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 671334
700 1 $a Singh, Richa. $3 1102872
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Advances in intelligent systems and computing ; $v 173. $3 884093
856 4 0 $u http://dx.doi.org/10.1007/978-81-322-2625-3
950 $a Engineering (Springer-11647)