Content Based Image Classification
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Content Based Image Classification
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Author : Rik Das
language : en
Publisher: CRC Press
Release Date : 2020-12-17
Content Based Image Classification written by Rik Das and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-17 with Computers categories.
Content-Based Image Classification: Efficient Machine Learning Using Robust Feature Extraction Techniques is a comprehensive guide to research with invaluable image data. Social Science Research Network has revealed that 65% of people are visual learners. Research data provided by Hyerle (2000) has clearly shown 90% of information in the human brain is visual. Thus, it is no wonder that visual information processing in the brain is 60,000 times faster than text-based information (3M Corporation, 2001). Recently, we have witnessed a significant surge in conversing with images due to the popularity of social networking platforms. The other reason for embracing usage of image data is the mass availability of high-resolution cellphone cameras. Wide usage of image data in diversified application areas including medical science, media, sports, remote sensing, and so on, has spurred the need for further research in optimizing archival, maintenance, and retrieval of appropriate image content to leverage data-driven decision-making. This book demonstrates several techniques of image processing to represent image data in a desired format for information identification. It discusses the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Image feature extraction with novel handcrafted techniques (traditional feature extraction) Image feature extraction with automated techniques (representation learning with CNNs) Significance of fusion-based approaches in enhancing classification accuracy MATLAB® codes for implementing the techniques Use of the Open Access data mining tool WEKA for multiple tasks The book is intended for budding researchers, technocrats, engineering students, and machine learning/deep learning enthusiasts who are willing to start their computer vision journey with content-based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means for insight generation. Readers will learn coding techniques necessary to propose novel mechanisms and disruptive approaches. The WEKA guide provided is beneficial for those uncomfortable coding for machine learning algorithms. The WEKA tool assists the learner in implementing machine learning algorithms with the click of a button. Thus, this book will be a stepping-stone for your machine learning journey. Please visit the author's website for any further guidance at https://www.rikdas.com/
Computer Vision Methods For Fast Image Classification And Retrieval
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Author : Rafał Scherer
language : en
Publisher: Springer
Release Date : 2019-01-29
Computer Vision Methods For Fast Image Classification And Retrieval written by Rafał Scherer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-29 with Computers categories.
The book presents selected methods for accelerating image retrieval and classification in large collections of images using what are referred to as ‘hand-crafted features.’ It introduces readers to novel rapid image description methods based on local and global features, as well as several techniques for comparing images. Developing content-based image comparison, retrieval and classification methods that simulate human visual perception is an arduous and complex process. The book’s main focus is on the application of these methods in a relational database context. The methods presented are suitable for both general-type and medical images. Offering a valuable textbook for upper-level undergraduate or graduate-level courses on computer science or engineering, as well as a guide for computer vision researchers, the book focuses on techniques that work under real-world large-dataset conditions.
Multimedia Information Retrieval And Management
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Author : David Feng
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Multimedia Information Retrieval And Management written by David Feng and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Technology & Engineering categories.
Multimedia information technologies, which provide comprehensive and intuitive information for a broad range of applications, have a strong impact on modem life, and have changed our way of learning and thinking. Over the past two decades, there has been an explosive growth in the use of digital multimedia (including audio, video, images and graphics) over the Internet and wireless communication. As the use of digital multimedia increases, effective data storage and management become increasingly important. In fields which use large quantities of data (e. g. audio, video, image and digital libraries; geographical and medical image databases; etc), we need to minimize the volume of data stored while meeting the often conflicting demand for accurate data representation. In addition, the data need to be managed such that it facilitates efficient searching, browsing and cooperative work. This area has been a very active research area in recent years. This book will provide readers with an up-to-date and comprehensive picture of cutting edge technologies in multimedia information retrieval and management, which directly affect our industry, economy and social life The book is divided into two major parts: Technological Fundamentals which covers the core theories of the area; and Applications which describes the broad range of practical uses for this technology.
Phishing Detection Using Content Based Image Classification
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Author : Shekhar Khandelwal
language : en
Publisher: CRC Press
Release Date : 2022-06-01
Phishing Detection Using Content Based Image Classification written by Shekhar Khandelwal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Phishing Detection Using Content-Based Image Classification is an invaluable resource for any deep learning and cybersecurity professional and scholar trying to solve various cybersecurity tasks using new age technologies like Deep Learning and Computer Vision. With various rule-based phishing detection techniques at play which can be bypassed by phishers, this book provides a step-by-step approach to solve this problem using Computer Vision and Deep Learning techniques with significant accuracy. The book offers comprehensive coverage of the most essential topics, including: Programmatically reading and manipulating image data Extracting relevant features from images Building statistical models using image features Using state-of-the-art Deep Learning models for feature extraction Build a robust phishing detection tool even with less data Dimensionality reduction techniques Class imbalance treatment Feature Fusion techniques Building performance metrics for multi-class classification task Another unique aspect of this book is it comes with a completely reproducible code base developed by the author and shared via python notebooks for quick launch and running capabilities. They can be leveraged for further enhancing the provided models using new advancement in the field of computer vision and more advanced algorithms.
Content Based Image And Video Retrieval
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Author : Oge Marques
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-04-30
Content Based Image And Video Retrieval written by Oge Marques and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-04-30 with Computers categories.
Content-Based Image And Video Retrieval addresses the basic concepts and techniques for designing content-based image and video retrieval systems. It also discusses a variety of design choices for the key components of these systems. This book gives a comprehensive survey of the content-based image retrieval systems, including several content-based video retrieval systems. The survey includes both research and commercial content-based retrieval systems. Content-Based Image And Video Retrieval includes pointers to two hundred representative bibliographic references on this field, ranging from survey papers to descriptions of recent work in the area, entire books and more than seventy websites. Finally, the book presents a detailed case study of designing MUSE–a content-based image retrieval system developed at Florida Atlantic University in Boca Raton, Florida.
Content Based Image Retrieval
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Author : Vipin Tyagi
language : en
Publisher: Springer
Release Date : 2018-01-15
Content Based Image Retrieval written by Vipin Tyagi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-15 with Computers categories.
The book describes several techniques used to bridge the semantic gap and reflects on recent advancements in content-based image retrieval (CBIR). It presents insights into and the theoretical foundation of various essential concepts related to image searches, together with examples of natural and texture image types. The book discusses key challenges and research topics in the context of image retrieval, and provides descriptions of various image databases used in research studies. The area of image retrieval, and especially content-based image retrieval (CBIR), is a very exciting one, both for research and for commercial applications. The book explains the low-level features that can be extracted from an image (such as color, texture, shape) and several techniques used to successfully bridge the semantic gap in image retrieval, making it a valuable resource for students and researchers interested in the area of CBIR alike.
Feature Dimension Reduction For Content Based Image Identification
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Author : Das, Rik
language : en
Publisher: IGI Global
Release Date : 2018-06-29
Feature Dimension Reduction For Content Based Image Identification written by Das, Rik and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-29 with Computers categories.
Image data has portrayed immense potential as a foundation of information for numerous applications. Recent trends in multimedia computing have witnessed a rapid growth in digital image collections, resulting in a need for increased image data management. Feature Dimension Reduction for Content-Based Image Identification is a pivotal reference source that explores the contemporary trends and techniques of content-based image recognition. Including research covering topics such as feature extraction, fusion techniques, and image segmentation, this book explores different theories to facilitate timely identification of image data and managing, archiving, maintaining, and extracting information. This book is ideally designed for engineers, IT specialists, researchers, academicians, and graduate-level students seeking interdisciplinary research on image processing and analysis.
Proceedings Of International Conference On Computer Vision And Image Processing
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Author : Balasubramanian Raman
language : en
Publisher: Springer
Release Date : 2016-12-23
Proceedings Of International Conference On Computer Vision And Image Processing written by Balasubramanian Raman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-23 with Technology & Engineering categories.
This edited volume contains technical contributions in the field of computer vision and image processing presented at the First International Conference on Computer Vision and Image Processing (CVIP 2016). The contributions are thematically divided based on their relation to operations at the lower, middle and higher levels of vision systems, and their applications. The technical contributions in the areas of sensors, acquisition, visualization and enhancement are classified as related to low-level operations. They discuss various modern topics – reconfigurable image system architecture, Scheimpflug camera calibration, real-time autofocusing, climate visualization, tone mapping, super-resolution and image resizing. The technical contributions in the areas of segmentation and retrieval are classified as related to mid-level operations. They discuss some state-of-the-art techniques – non-rigid image registration, iterative image partitioning, egocentric object detection and video shot boundary detection. The technical contributions in the areas of classification and retrieval are categorized as related to high-level operations. They discuss some state-of-the-art approaches – extreme learning machines, and target, gesture and action recognition. A non-regularized state preserving extreme learning machine is presented for natural scene classification. An algorithm for human action recognition through dynamic frame warping based on depth cues is given. Target recognition in night vision through convolutional neural network is also presented. Use of convolutional neural network in detecting static hand gesture is also discussed. Finally, the technical contributions in the areas of surveillance, coding and data security, and biometrics and document processing are considered as applications of computer vision and image processing. They discuss some contemporary applications. A few of them are a system for tackling blind curves, a quick reaction target acquisition and tracking system, an algorithm to detect for copy-move forgery based on circle block, a novel visual secret sharing scheme using affine cipher and image interleaving, a finger knuckle print recognition system based on wavelet and Gabor filtering, and a palmprint recognition based on minutiae quadruplets.
Artificial Intelligence For Maximizing Content Based Image Retrieval
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Author : Ma, Zongmin
language : en
Publisher: IGI Global
Release Date : 2009-01-31
Artificial Intelligence For Maximizing Content Based Image Retrieval written by Ma, Zongmin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-31 with Computers categories.
Discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field.
Lecture Notes In Real Time Intelligent Systems
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Author : Jolanta Mizera-Pietraszko
language : en
Publisher:
Release Date : 2019
Lecture Notes In Real Time Intelligent Systems written by Jolanta Mizera-Pietraszko and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with COMPUTERS categories.
The second volume of the book series highlights works presented at the 2nd International Conference on Real Time Intelligent Systems, held in Casablanca on October 18-20, 2017 . The book offers a comprehensive, practical review of the state-of-the-art in designing and implementing real-time intelligent computing for the areas within the conference's scope such as robotics, intelligent alert systems, IoT, remote access control, multi-agent systems, networking, mobile smart systems, crowdsourcing, broadband systems, cloud computing, streaming data and many other applications. Research in real-time computing supports decision making in dynamic environments. Some examples include ABS, FBW flight control, automatic air-conditioning, etc. Intelligent computing relies heavily on artificial intelligence (AI) to make computers act for humans. The authors are confident that the solutions discussed in this book will provide a unique source of information and inspiration for researchers working in AI, distributed coding algorithms or smart services and platforms, and for IT professionals, who can integrate the proposed methods into their practice.