Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments

Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments PDF Author: Marcin Woźniak
Publisher: MDPI
ISBN: 3036512683
Category : Technology & Engineering
Languages : en
Pages : 454

Get Book Here

Book Description
Recent years have seen a vast development in various methodologies for object detection and feature extraction and recognition, both in theory and in practice. When processing images, videos, or other types of multimedia, one needs efficient solutions to perform fast and reliable processing. Computational intelligence is used for medical screening where the detection of disease symptoms is carried out, in prevention monitoring to detect suspicious behavior, in agriculture systems to help with growing plants and animal breeding, in transportation systems for the control of incoming and outgoing transportation, for unmanned vehicles to detect obstacles and avoid collisions, in optics and materials for the detection of surface damage, etc. In many cases, we use developed techniques which help us to recognize some special features. In the context of this innovative research on computational intelligence, the Special Issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments” present an excellent opportunity for the dissemination of recent results and achievements for further innovations and development. It is my pleasure to present this collection of excellent contributions to the research community. - Prof. Marcin Woźniak, Silesian University of Technology, Poland –

Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments

Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments PDF Author: Marcin Woźniak
Publisher: MDPI
ISBN: 3036512683
Category : Technology & Engineering
Languages : en
Pages : 454

Get Book Here

Book Description
Recent years have seen a vast development in various methodologies for object detection and feature extraction and recognition, both in theory and in practice. When processing images, videos, or other types of multimedia, one needs efficient solutions to perform fast and reliable processing. Computational intelligence is used for medical screening where the detection of disease symptoms is carried out, in prevention monitoring to detect suspicious behavior, in agriculture systems to help with growing plants and animal breeding, in transportation systems for the control of incoming and outgoing transportation, for unmanned vehicles to detect obstacles and avoid collisions, in optics and materials for the detection of surface damage, etc. In many cases, we use developed techniques which help us to recognize some special features. In the context of this innovative research on computational intelligence, the Special Issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments” present an excellent opportunity for the dissemination of recent results and achievements for further innovations and development. It is my pleasure to present this collection of excellent contributions to the research community. - Prof. Marcin Woźniak, Silesian University of Technology, Poland –

Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments

Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments PDF Author: Marcin Woźniak
Publisher:
ISBN: 9783036512693
Category :
Languages : en
Pages : 454

Get Book Here

Book Description
Recent years have seen a vast development in various methodologies for object detection and feature extraction and recognition, both in theory and in practice. When processing images, videos, or other types of multimedia, one needs efficient solutions to perform fast and reliable processing. Computational intelligence is used for medical screening where the detection of disease symptoms is carried out, in prevention monitoring to detect suspicious behavior, in agriculture systems to help with growing plants and animal breeding, in transportation systems for the control of incoming and outgoing transportation, for unmanned vehicles to detect obstacles and avoid collisions, in optics and materials for the detection of surface damage, etc. In many cases, we use developed techniques which help us to recognize some special features. In the context of this innovative research on computational intelligence, the Special Issue “Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments” present an excellent opportunity for the dissemination of recent results and achievements for further innovations and development. It is my pleasure to present this collection of excellent contributions to the research community. - Prof. Marcin Woźniak, Silesian University of Technology, Poland -

Artificial Intelligence for Smart Healthcare

Artificial Intelligence for Smart Healthcare PDF Author: Parul Agarwal
Publisher: Springer Nature
ISBN: 3031236025
Category : Technology & Engineering
Languages : en
Pages : 527

Get Book Here

Book Description
This book provides information on interdependencies of medicine and telecommunications engineering and how the two must rely on each other to effectively function in this era. The book discusses new techniques for medical service improvisation such as clear-cut views on medical technologies. The authors provide chapters on communication essentiality in healthcare, processing of medical amenities using medical images, the importance of data and information technology in medicine, and machine learning and artificial intelligence in healthcare. Authors include researchers, academics, and professionals in the field.

Machine Learning in Computer Vision

Machine Learning in Computer Vision PDF Author: Nicu Sebe
Publisher: Springer Science & Business Media
ISBN: 1402032757
Category : Computers
Languages : en
Pages : 253

Get Book Here

Book Description
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.

Smart Wearable Devices in Healthcare—Methodologies, Applications, and Algorithms

Smart Wearable Devices in Healthcare—Methodologies, Applications, and Algorithms PDF Author: Chang Yan
Publisher: Frontiers Media SA
ISBN: 2832540082
Category : Science
Languages : en
Pages : 127

Get Book Here

Book Description
Wearable health devices have been an emerging technology that enables an ambulatory acquisition of physiological signals to monitor health status over a long time (hours/days/weeks/years) inside and outside clinical environments. Big data and deep learning, in particular, are receiving a lot of attention in this rapidly growing digital health community. A key benefit of deep learning is to analyze and learn massive amounts of data, which makes it especially valuable in healthcare since raw data is largely gathered from personalized wearable health devices. A wide range of users may benefit from unobstructed and even remote monitoring of pertinent or vital signs, which makes it easier to detect life-threatening diseases early, track the progression of pathologies and stress levels, evaluate the efficacy of therapies, provide low-cost and reliable diagnoses, etc. Today’s personal health devices have provided an amazing insight into people’s health and wellness, which allow clinicians to use these smart wearables to collect and analyze measuring data like electroencephalogram (EEG), electrocardiogram (ECG or EKG), respiration, heart rate, temperature level, blood oxygen, and blood pressure for health monitoring or clinical trials. This Research Topic mainly focuses on the technical revolution in wearable health systems, which aims to design more smart and useful wearables, contributing to a substantial change in the methodologies, applications, and algorithms of machine learning for wearable health devices. With the help of deep learning and sensor fusion capabilities from wearable health platforms, this data will be used more effectively, which can help to construct smart, novel, specific solutions to improve the quality of healthcare and capabilities of utilizing new deep learning technologies.

Practical Machine Learning and Image Processing

Practical Machine Learning and Image Processing PDF Author: Himanshu Singh
Publisher: Apress
ISBN: 1484241495
Category : Computers
Languages : en
Pages : 177

Get Book Here

Book Description
Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application. What You Will LearnDiscover image-processing algorithms and their applications using Python Explore image processing using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms for image processing Apply image-processing techniques to five real-time projects Who This Book Is For Data scientists and software developers interested in image processing and computer vision.

Handbook of Research on Computerized Occlusal Analysis Technology Applications in Dental Medicine

Handbook of Research on Computerized Occlusal Analysis Technology Applications in Dental Medicine PDF Author: Kerstein, DMD, Robert B.
Publisher: IGI Global
ISBN: 1466665882
Category : Medical
Languages : en
Pages : 1070

Get Book Here

Book Description
Modern medicine is changing drastically as new technologies emerge to transform the way in which patients are diagnosed, treated, and monitored. In particular, dental medicine is experiencing a tremendous shift as new digital innovations are integrated into dental practice. The Handbook of Research on Computerized Occlusal Analysis Technology Applications in Dental Medicine explores the use of digital tools in dentistry, including their evolution as well as evidence-based research on the benefits of technological tools versus non-digital occlusal indicators. Comprised of current research on clinical applications and technologies, this publication is ideal for use by clinicians, educators, and upper-level students in dentistry.

Computer Vision Applications

Computer Vision Applications PDF Author: Chetan Arora
Publisher: Springer Nature
ISBN: 9811513872
Category : Computers
Languages : en
Pages : 138

Get Book Here

Book Description
This book constitutes the refereed proceedings of the third Workshop on Computer Vision Applications, WCVA 2018, held in Conjunction with ICVGIP 2018, in Hyderabad, India, in December 2018. The 10 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers focus on computer vision; industrial applications; medical applications; and social applications.

Deep Learning for Computer Vision

Deep Learning for Computer Vision PDF Author: Jason Brownlee
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 564

Get Book Here

Book Description
Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.

Feature Extraction and Image Processing for Computer Vision

Feature Extraction and Image Processing for Computer Vision PDF Author: Mark Nixon
Publisher: Academic Press
ISBN: 0123978246
Category : Computers
Languages : en
Pages : 629

Get Book Here

Book Description
Feature Extraction and Image Processing for Computer Vision is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in Matlab. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated. As one reviewer noted, "The main strength of the proposed book is the exemplar code of the algorithms." Fully updated with the latest developments in feature extraction, including expanded tutorials and new techniques, this new edition contains extensive new material on Haar wavelets, Viola-Jones, bilateral filtering, SURF, PCA-SIFT, moving object detection and tracking, development of symmetry operators, LBP texture analysis, Adaboost, and a new appendix on color models. Coverage of distance measures, feature detectors, wavelets, level sets and texture tutorials has been extended. - Named a 2012 Notable Computer Book for Computing Methodologies by Computing Reviews - Essential reading for engineers and students working in this cutting-edge field - Ideal module text and background reference for courses in image processing and computer vision - The only currently available text to concentrate on feature extraction with working implementation and worked through derivation