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Author: Bir Bhanu
Publisher: Springer Science & Business Media
ISBN: 1461527740
Category : Computers
Languages : en
Pages : 283
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Book Description
Image segmentation is generally the first task in any automated image understanding application, such as autonomous vehicle navigation, object recognition, photointerpretation, etc. All subsequent tasks, such as feature extraction, object detection, and object recognition, rely heavily on the quality of segmentation. One of the fundamental weaknesses of current image segmentation algorithms is their inability to adapt the segmentation process as real-world changes are reflected in the image. Only after numerous modifications to an algorithm's control parameters can any current image segmentation technique be used to handle the diversity of images encountered in real-world applications. Genetic Learning for Adaptive Image Segmentation presents the first closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year, weather, etc. Image segmentation performance is evaluated using multiple measures of segmentation quality. These quality measures include global characteristics of the entire image as well as local features of individual object regions in the image. This adaptive image segmentation system provides continuous adaptation to normal environmental variations, exhibits learning capabilities, and provides robust performance when interacting with a dynamic environment. This research is directed towards adapting the performance of a well known existing segmentation algorithm (Phoenix) across a wide variety of environmental conditions which cause changes in the image characteristics. The book presents a large number of experimental results and compares performance with standard techniques used in computer vision for both consistency and quality of segmentation results. These results demonstrate, (a) the ability to adapt the segmentation performance in both indoor and outdoor color imagery, and (b) that learning from experience can be used to improve the segmentation performance over time.
Author: Bir Bhanu
Publisher: Springer Science & Business Media
ISBN: 1461527740
Category : Computers
Languages : en
Pages : 283
Get Book Here
Book Description
Image segmentation is generally the first task in any automated image understanding application, such as autonomous vehicle navigation, object recognition, photointerpretation, etc. All subsequent tasks, such as feature extraction, object detection, and object recognition, rely heavily on the quality of segmentation. One of the fundamental weaknesses of current image segmentation algorithms is their inability to adapt the segmentation process as real-world changes are reflected in the image. Only after numerous modifications to an algorithm's control parameters can any current image segmentation technique be used to handle the diversity of images encountered in real-world applications. Genetic Learning for Adaptive Image Segmentation presents the first closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year, weather, etc. Image segmentation performance is evaluated using multiple measures of segmentation quality. These quality measures include global characteristics of the entire image as well as local features of individual object regions in the image. This adaptive image segmentation system provides continuous adaptation to normal environmental variations, exhibits learning capabilities, and provides robust performance when interacting with a dynamic environment. This research is directed towards adapting the performance of a well known existing segmentation algorithm (Phoenix) across a wide variety of environmental conditions which cause changes in the image characteristics. The book presents a large number of experimental results and compares performance with standard techniques used in computer vision for both consistency and quality of segmentation results. These results demonstrate, (a) the ability to adapt the segmentation performance in both indoor and outdoor color imagery, and (b) that learning from experience can be used to improve the segmentation performance over time.
Author: Donald Davendra
Publisher: Springer
ISBN: 3319281615
Category : Technology & Engineering
Languages : en
Pages : 294
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Book Description
This book brings together the current state of-the-art research in Self Organizing Migrating Algorithm (SOMA) as a novel population-based evolutionary algorithm, modeled on the predator-prey relationship, by its leading practitioners. As the first ever book on SOMA, this book is geared towards graduate students, academics and researchers, who are looking for a good optimization algorithm for their applications. This book presents the methodology of SOMA, covering both the real and discrete domains, and its various implementations in different research areas. The easy-to-follow and implement methodology used in the book will make it easier for a reader to implement, modify and utilize SOMA.
Author: Vikrant Bhateja
Publisher: Springer Nature
ISBN: 9811509476
Category : Technology & Engineering
Languages : en
Pages : 880
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Book Description
This book gathers selected research papers presented at the First International Conference on Embedded Systems and Artificial Intelligence (ESAI 2019), held at Sidi Mohamed Ben Abdellah University, Fez, Morocco, on 2–3 May 2019. Highlighting the latest innovations in Computer Science, Artificial Intelligence, Information Technologies, and Embedded Systems, the respective papers will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.
Author: Stefano Cagnoni
Publisher: Hindawi Publishing Corporation
ISBN: 9774540018
Category : Computer vision
Languages : en
Pages : 473
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Book Description
Author: Bhattacharyya, Siddhartha
Publisher: IGI Global
ISBN: 1466625198
Category : Computers
Languages : en
Pages : 535
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Book Description
Using the same strategy for the needs of image processing and pattern recognition, scientists and researchers have turned to computational intelligence for better research throughputs and end results applied towards engineering, science, business and financial applications. Handbook of Research on Computational Intelligence for Engineering, Science, and Business discusses the computation intelligence approaches, initiatives and applications in the engineering, science and business fields. This reference aims to highlight computational intelligence as no longer limited to computing-related disciplines and can be applied to any effort which handles complex and meaningful information.
Author: Gregory J. Hamlin
Publisher: Springer Science & Business Media
ISBN: 1461554713
Category : Computers
Languages : en
Pages : 186
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Book Description
Robotic systems are characterized by the intersection of computer intelligence with the physical world. This blend of physical reasoning and computational intelligence is well illustrated by the Tetrobot study described in this book. Tetrobot: A Modular Approach to Reconfigurable Parallel Robotics describes a new approach to the design of robotic systems. The Tetrobot approach utilizes modular components which may be reconfigured into many different mechanisms which are suited to different applications. The Tetrobot system includes two unique contributions: a new mechanism (a multilink spherical joint design), and a new control architecture based on propagation of kinematic solutions through the structure. The resulting Tetrobot system consists of fundamental components which may be mechanically reassembled into any modular configuration, and the control architecture will provide position control of the resulting structure. A prototype Tetrobot system has been built and evaluated experimentally. Tetrobot arms, platforms, and walking machines have been built and controlled in a variety of motion and loading conditions. The Tetrobot system has applications in a variety of domains where reconfiguration, flexibility, load capacity, and failure recovery are important aspects of the task. A number of key research directions have been opened by the Tetrobot research activities. Continuing topics of interest include: development of a more distributed implementation of the computer control architecture, analysis of the dynamics of the Tetrobot system motion for improved control of high-speed motions, integration of sensor systems to control the motion and shape of the high-dimensionality systems, and exploration of self-reconfiguration of the system. Tetrobot: A Modular Approach to Reconfigurable Parallel Robotics will be of interest to research workers, specialists and professionals in the areas of robotics, mechanical systems and computer engineering.
Author: Niranjan N. Chiplunkar
Publisher: Springer Nature
ISBN: 9811535140
Category : Technology & Engineering
Languages : en
Pages : 1456
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Book Description
This book presents selected peer-reviewed papers from the International Conference on Artificial Intelligence and Data Engineering (AIDE 2019). The topics covered are broadly divided into four groups: artificial intelligence, machine vision and robotics, ambient intelligence, and data engineering. The book discusses recent technological advances in the emerging fields of artificial intelligence, machine learning, robotics, virtual reality, augmented reality, bioinformatics, intelligent systems, cognitive systems, computational intelligence, neural networks, evolutionary computation, speech processing, Internet of Things, big data challenges, data mining, information retrieval, and natural language processing. Given its scope, this book can be useful for students, researchers, and professionals interested in the growing applications of artificial intelligence and data engineering.
Author: Julian F. Miller
Publisher: Springer Science & Business Media
ISBN: 3642173101
Category : Computers
Languages : en
Pages : 358
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Book Description
Cartesian Genetic Programming (CGP) is a highly effective and increasingly popular form of genetic programming. It represents programs in the form of directed graphs, and a particular characteristic is that it has a highly redundant genotype–phenotype mapping, in that genes can be noncoding. It has spawned a number of new forms, each improving on the efficiency, among them modular, or embedded, CGP, and self-modifying CGP. It has been applied to many problems in both computer science and applied sciences. This book contains chapters written by the leading figures in the development and application of CGP, and it will be essential reading for researchers in genetic programming and for engineers and scientists solving applications using these techniques. It will also be useful for advanced undergraduates and postgraduates seeking to understand and utilize a highly efficient form of genetic programming.
Author: Siddhartha Bhattacharyya
Publisher: Springer
ISBN: 3319776258
Category : Computers
Languages : en
Pages : 263
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Book Description
This book presents contributions in the field of computational intelligence for the purpose of image analysis. The chapters discuss how problems such as image segmentation, edge detection, face recognition, feature extraction, and image contrast enhancement can be solved using techniques such as genetic algorithms and particle swarm optimization. The contributions provide a multidimensional approach, and the book will be useful for researchers in computer science, electrical engineering, and information technology.
Author: Chris Leger
Publisher: Springer Science & Business Media
ISBN: 1461543312
Category : Technology & Engineering
Languages : en
Pages : 280
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Book Description
Darwin2K: An Evolutionary Approach to Automated Design for Robotics is an essential reference tool for researchers, professionals, and students involved in robot design or in evolutionary synthesis, design, and optimization. It is also necessary for users of Darwin2K. Researchers and hobbyists interested in genetic algorithms and artificial life techniques will find the book interesting. The primary purpose of this book is to describe a methodology for using computers to automatically design robots to meet the specific needs of an application. Details of many novel aspects of the methodology are presented, including an evolutionary algorithm for synthesizing and optimizing multiple objective functions, an algorithm for dynamic simulation of arbitrary robots, an extensible software architecture, and a new representation for robots that is appropriate for robot design. The methodology as a whole is significant in terms of its impact on robot design practices, and as a case study in building evolutionary design systems. Individual parts of the systems are also relevant to other areas. For example, the evolutionary algorithm can be used for design and optimization problems other than robotics, and the dynamic simulation algorithm can be used for analysis and simulation of existing robots or as a part of a manual design tool. The book also gives an overview of previous work in automated design of robots, and of evolutionary design in other engineering disciplines.
