Details

Hybrid Intelligence for Image Analysis and Understanding


Hybrid Intelligence for Image Analysis and Understanding


1. Aufl.

von: Siddhartha Bhattacharyya, Indrajit Pan, Anirban Mukherjee, Paramartha Dutta

100,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 27.07.2017
ISBN/EAN: 9781119242956
Sprache: englisch
Anzahl Seiten: 464

DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.

Beschreibungen

A synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding. The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis. Key features: Provides in-depth analysis of hybrid intelligent paradigms. Divided into self-contained chapters. Provides ample case studies, illustrations and photographs of real-life examples to illustrate findings and applications of different hybrid intelligent paradigms. Offers new solutions to recent problems in computer science, specifically in the application of hybrid intelligent techniques for image analysis and understanding, using well-known contemporary algorithms. The book is essential reading for lecturers, researchers and graduate students in electrical engineering and computer science.
Editor Biographies List of Contributors Foreword Preface About the companion website Chapter 1 Multilevel image segmentation using Modified Genetic Algorithm (MfGA) based Fuzzy C-means Sourav De, Sunanda Das, Siddhartha Bhattacharyya, Paramartha Dutta Chapter 2 Character Recognition Using Entropy-based Fuzzy C-Means Clustering B. Kondalarao, S. Sahoo, D. K. Pratihar Chapter 3 A Two-stage Approach to Handwritten Indic Script Identification Pawan Kumar Singh, Supratim Das, Ram Sarkar, Mita Nasipuri Chapter 4 Feature extraction and segmentation techniques in static hand gesture recognition system Subhamoy Chatterjee, Piyush Bhandari, Mahesh Kumar Kolekar Chapter 5 SVM combination for an enhanced prediction of writer’s soft-biometrics Nesrine Bouadjenek, Hassiba Nemmour, Youcef Chibani Chapter 6 Brain Inspired Machine Intelligence for Image Analysis: Convolutional Neural Networks Siddharth Srivastava, Brejesh Lall Chapter 7 Human behavioral analysis using evolutionary algorithms and deep learning Earnest Paul Ijjina, C. Krishna Mohan Chapter 8 Feature Based Robust Description and Monocular Detection, An Application To Vehicle Tracking Ramazan Yyldyz, Tankut Acarman Chapter 9 A GIS Anchored Technique for Social Utility Hot Spot Detection Anirban Chakraborty, J. K. Mandal, Arnab Patra, Jayatra Majumdar Chapter 10 Hyperspectral data processing—Spectral Unmixing, Classification and Target Identification Vaibhav Lodhi, Debashish Chakravarty, Pabitra Mitra Chapter 11 A hybrid approach for band selection of hyperspectral images Aditi Roy Chowdhury, Joydev Hazra, Paramartha Dutta Chapter 12 Uncertainty Based Clustering Algorithms for Medical Image Analysis B. K. Tripathy, Deepthi P. Hudedagaddi Chapter 13 An Optimized Breast Cancer Diagnosis System Using Cuckoo Search Algorithm and Support Vector Machine classifier Prabukumar. M, Agilandeeswari. L, Arun Kumar Sangaiah Chapter 14 Analysis of Hand vein images using Hybrid techniques R. Sudhakar, S. Bharathi, V. Gurunathan Chapter 15 Identification of Abnormal Masses in Digital Mammogram using Statistical Decision Making Indra Kanta Maitra, Sangita Bhattacharjee, Samir Kumar Bandyopadhyay Chapter 16 Automatic Detection of Coronary Artery Stenosis using Bayesian Classification and Gaussian Filters based on Differential Evolution Ivan Cruz-Aceves, Fernando Cervantes-Sanchez, Arturo Hernandez-Aguirre Chapter 17Evaluating the Efficacy of Multi-resolution Texture Features for Prediction of Breast Density using Mammographic Images Kriti Virmani, Jitendra Virmani
PROF. (DR.) SIDDHARTHA BHATTACHARYYA (SMIEEE, SMACM, LMCSI, LMOSI, LMISTE, MIAENG, MIRSS, MACSE, MIAASSE) obtained his Bachelors in Physics, Optics and Optoelectronics and Masters in Optics and Optoelectronics from the University of Calcutta, India, in 1995, 1998 and 2000 respectively. He completed a PhD in Computer Science and Engineering from Jadavpur University, India, in 2008. He is currently the Professor and Head of Information Technology at the RCC Institute of Information Technology, Kolkata, India. He is also the Dean (Research & Development) of the institute. He is a co-author of 3 books and co-editor of 5 books and more than 135 research publications. DR. INDRAJIT PAN did his Bachelors in Computer Science Engineering in 2005 at The University of Burdwan, India, and completed his Masters in Information Technology at Bengal Engineering and Science University, Shibpur. He got a University Medal for his performance in his Masters. Later, he was awarded a PhD in Engineering from the Indian Institute of Engineering, Science and Technology (IIEST). He has more than 10 years' experience teaching in undergraduate and postgraduate engineering in IT and allied field. Currently, he is an Assistant Professor of Information Technology at the RCC Institute of Information Technology. His research interests include CAD, Computer Security, Soft Computing Applications and Cloud Computing. DR. ANIRBAN MUKHERJEE did his Bachelors in Civil Engineering in 1994 at Jadavpur University, Kolkata. He completed his PhD on 'Automatic Diagram Drawing based on Natural Language Text Understanding' at the Indian Institute of Engineering, Science and Technology (IIEST), Shibpur, in 2014. He has more than 20 years' experience in teaching undergraduate and postgraduate engineering in IT and allied field. Currently, he is an Associate Professor and HOD of Engineering Science & Management at the RCC Institute of Information Technology. He has experience of working in computer aided design and engineering analysis and also of teaching on CAD courses. His research interests include Computer Graphics & CAD, Soft Computing Applications and Assistive Technology. He has co-authored two UG engineering textbooks: a popular one on 'Computer Graphics and Multimedia' and another on 'Engineering Mechanics'. He has also co-authored more than 15 books on Computer Graphics/Multimedia for distance learning professional courses at different Universities in India. PROF. (DR.) PARAMARTHA DUTTA has a B. Stat. (Hons.), M. Stat., M. Tech in Computer Science, and a PhD (Engineering) in Computer Science and Technology. With around 23 years of research and academic experience, Professor Dutta is currently serving as a Professor in the Department of Computer and System Sciences, Visva Bharati University. Professor Dutta is a senior Member of IEEE and ACM. He has executed almost 200 projects funded by the Govt. of India. Professor Dutta has remained associated with various Universities and Institutes as Visiting/Guest faculty. To date, Professor Dutta has more than 6 authored and 6 edited books in addition to around 180 papers, published in different International Journals and in International/National conference proceedings.
A synergy of techniques on hybrid intelligence for real-life image analysis Hybrid Intelligence for Image Analysis and Understanding brings together research on the latest results and progress in the development of hybrid intelligent techniques for faithful image analysis and understanding. As such, the focus is on the methods of computational intelligence, with an emphasis on hybrid intelligent methods applied to image analysis and understanding. The book offers a diverse range of hybrid intelligence techniques under the umbrellas of image thresholding, image segmentation, image analysis and video analysis. Key features: Provides in-depth analysis of hybrid intelligent paradigms. Provides ample case studies, illustrations and photographs of real-life examples to illustrate findings and applications of different hybrid intelligent paradigms. Offers new solutions to recent problems in computer science, specifically in the application of hybrid intelligent techniques for image analysis and understanding, using well-known contemporary algorithms. The book is an essential reference for lecturers, researchers and graduate students in electrical engineering and computer science specializing in image processing or computational intelligence.

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