Pattern Recognition And Big Data

Pattern Recognition And Big Data

by Sankar Kumar Pal, Amita Pal
ISBN-10:
9813144548
ISBN-13:
9789813144545
Pub. Date:
02/03/2017
Publisher:
World Scientific Publishing Company, Incorporated
ISBN-10:
9813144548
ISBN-13:
9789813144545
Pub. Date:
02/03/2017
Publisher:
World Scientific Publishing Company, Incorporated
Pattern Recognition And Big Data

Pattern Recognition And Big Data

by Sankar Kumar Pal, Amita Pal
$315.0 Current price is , Original price is $315.0. You
$315.00 
  • SHIP THIS ITEM
    Qualifies for Free Shipping
  • PICK UP IN STORE
    Check Availability at Nearby Stores

Overview

Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications.Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.

Product Details

ISBN-13: 9789813144545
Publisher: World Scientific Publishing Company, Incorporated
Publication date: 02/03/2017
Pages: 876
Product dimensions: 6.20(w) x 9.10(h) x 1.30(d)

Table of Contents

Preface vii

1 Pattern Recognition: Evolution, Mining and Big Data A. Pal S. K. Pal 1

2 Pattern Classification with Gaussian Processes V. Stathopoulos M. Girolami 37

3 Active Multitask Learning using Supervised and Shared Latent Topics A. Acharya R. J. Mooney J. Ghosh 75

4 Sparse and Low-Rank Models for Visual Domain Adaptation R. Chellappa V. M. Patel 113

5 Pattern Classification using the Principle of Parsimony: Two Examples J. Basak 135

6 Robust Learning of Classifiers in the Presence of Label Noise P. S. Sastry N. Manwani 167

7 Sparse Representation for Time-Series Classification S. Bahrampour N. M. Nasrabadi A. Ray 199

8 Fuzzy Sots as a Logic Canvas for Pattern Recognition W. Pedryez N. J. Pizzi 217

9 Optimizing Neural Network Structures to Match Pattern Recognition Task Complexity B. G. Gherman K. Sirlantzis F. Deravi 255

10 Multi-Criterion Optimization and Decision Making Using Evolutionary Computing K. Deb 293

11 Rough Sets in Pattern Recognition A. Skowron H. S. Nguyen A. Jankowski 323

12 The Twin SVM Minimizes the Total Risk Jayadeva S. Soman S. Chandra 395

13 Dynamic Kernels based Approaches to Analysis of Varying Length Patterns in Speech and Image Processing Tasks Veena T. Dileep A. D. C. Chandra Sekhar 407

14 Fuzzy Rough Granular Neural Networks for Pattern Analysis A. Ganivada S. S. Ray S. K. Pal 487

15 Fundamentals of Rough-Fuzzy Clustering and Its Application in Bioinformatics P. Maji S. Paul 513

16 Keygraphs: Structured Features for Object Detection and Applications M. Hashimoto H. Morimitsu R. Hirata-Jr R. M. Cesar-Jr. 545

17 Mining Multimodal Data S. Chaudhury L. Dey I. Verma E. Hassan 581

18 Solving Classification Problems on Human Epithelial Type 2 Cells for Anti-Nuclear Antibodies Test: Traditional versus Contemporary Approaches A. Wiliem B. C. Luvell 605

19 Representation Learning for Spoken Term Detection P. R. Reddy K. S. R. Murly B. Yegnanarayana 633

20 Tongue Pattern Recognition to Detect Diabetes Mellitus and Non-Proliferative Diabetic Retinopathy B. Zhang 663

21 Moving Object Detection using Multi-layer Markov Random Field Model B. N. Subudhi S. Ghosh A. Ghosh 687

22 Recent Advances in Remote Sensing Time Series Image Classification L. Bruzzone B. Dermir F. Bovolo 713

23 Sensor Selection for E-Nose Sunil T. T. S. Chaudhuri M. U. Sharma 735

24 Understanding the Usage of Idioms in Twitter Social Network K. Rudra A. Chakravarthy N. Ganguly S. Ghosh 767

25 Sampling Theorems for Twitter: Ideas from Large Deviation Theory D. Palguna V. Joshi V. Chakravarthy R. Kothari L. V. Subramaniam 789

26 A Machine-mind Architecture and Z*-numbers for Real-world Comprehension R. Banerjee S. K. Pal 805

Author Index 843

Subject Index 845

About the Editors 855

From the B&N Reads Blog

Customer Reviews