Image Processing Using Pulse Coupled Neural Networks

Author : Thomas Lindblad,Jason M. Kinser
Publisher : Springer Science & Business Media
Page : 164 pages
File Size : 40,5 Mb
Release : 2005-12-05
Category : Technology & Engineering
ISBN : 9783540282938

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Image Processing Using Pulse-Coupled Neural Networks by Thomas Lindblad,Jason M. Kinser Pdf

This is the first book to explain and demonstrate the tremendous ability of Pulse-Coupled Neural Networks (PCNNs) when applied to the field of image processing. PCNNs and their derivatives are biologically inspired models that are powerful tools for extracting texture, segments, and edges from images. As these attributes form the foundations of most image processing tasks, the use of PCNNs facilitates traditional tasks such as recognition, foveation, and image fusion. PCNN technology has also paved the way for new image processing techniques such as object isolation, spiral image fusion, image signatures, and content-based image searches. This volume contains examples of several image processing applications, as well as a review of hardware implementations.

Author : Thomas Lindblad,Jason M. Kinser
Publisher : Springer Science & Business Media
Page : 246 pages
File Size : 43,6 Mb
Release : 2013-05-13
Category : Technology & Engineering
ISBN : 9783642368776

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Image Processing using Pulse-Coupled Neural Networks by Thomas Lindblad,Jason M. Kinser Pdf

Image processing algorithms based on the mammalian visual cortex are powerful tools for extraction information and manipulating images. This book reviews the neural theory and translates them into digital models. Applications are given in areas of image recognition, foveation, image fusion and information extraction. The third edition reflects renewed international interest in pulse image processing with updated sections presenting several newly developed applications. This edition also introduces a suite of Python scripts that assist readers in replicating results presented in the text and to further develop their own applications.

Author : Thomas Lindblad,Jason Kinser
Publisher : Springer
Page : 164 pages
File Size : 49,9 Mb
Release : 2009-09-02
Category : Technology & Engineering
ISBN : 3540806504

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Image Processing Using Pulse-Coupled Neural Networks by Thomas Lindblad,Jason Kinser Pdf

Author : Yide Ma,Kun Zhan,Zhaobin Wang
Publisher : Springer Science & Business Media
Page : 206 pages
File Size : 44,9 Mb
Release : 2011-09-02
Category : Computers
ISBN : 9783642137457

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Applications of Pulse-Coupled Neural Networks by Yide Ma,Kun Zhan,Zhaobin Wang Pdf

"Applications of Pulse-Coupled Neural Networks" explores the fields of image processing, including image filtering, image segmentation, image fusion, image coding, image retrieval, and biometric recognition, and the role of pulse-coupled neural networks in these fields. This book is intended for researchers and graduate students in artificial intelligence, pattern recognition, electronic engineering, and computer science. Prof. Yide Ma conducts research on intelligent information processing, biomedical image processing, and embedded system development at the School of Information Science and Engineering, Lanzhou University, China.

Author : Thomas Lindblad,Jason Kinser
Publisher : Springer Science & Business Media
Page : 184 pages
File Size : 50,8 Mb
Release : 2005-08-02
Category : Technology & Engineering
ISBN : 354024218X

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Image Processing Using Pulse-Coupled Neural Networks by Thomas Lindblad,Jason Kinser Pdf

* Weitere Angaben Verfasser: Thomas Lindblad is a professor at the Royal Institute of Technology (Physics) in Stockholm. Working and teaching nuclear and environmental physics his main interest is with sensors, signal processing and intelligent data analysis of torrent data from experiments on-line accelerators, in space, etc. Jason Kinser is an associate professor at George Mason University. He has developed a plethora of image processing applications in the medical, military, and industrial fields. He has been responsible for the conversion of PCNN theory into practical applications providing many improvements in both speed and performance

Author : Himanshu Singh
Publisher : Apress
Page : 177 pages
File Size : 54,7 Mb
Release : 2019-02-26
Category : Computers
ISBN : 9781484241493

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Practical Machine Learning and Image Processing by Himanshu Singh Pdf

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.

Author : Yide Ma,Kun Zhan,Zhaobin Wang
Publisher : Unknown
Page : 199 pages
File Size : 46,6 Mb
Release : 2010
Category : Electronic
ISBN : 7040279789

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Applications of Pulse Coupled Neural Networks by Yide Ma,Kun Zhan,Zhaobin Wang Pdf

Author : Zhongliang Jing,Han Pan,Yuankai Li,Peng Dong
Publisher : Springer
Page : 340 pages
File Size : 47,7 Mb
Release : 2018-06-25
Category : Computers
ISBN : 9783319907161

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Non-Cooperative Target Tracking, Fusion and Control by Zhongliang Jing,Han Pan,Yuankai Li,Peng Dong Pdf

This book gives a concise and comprehensive overview of non-cooperative target tracking, fusion and control. Focusing on algorithms rather than theories for non-cooperative targets including air and space-borne targets, this work explores a number of advanced techniques, including Gaussian mixture cardinalized probability hypothesis density (CPHD) filter, optimization on manifold, construction of filter banks and tight frames, structured sparse representation, and others. Containing a variety of illustrative and computational examples, Non-cooperative Target Tracking, Fusion and Control will be useful for students as well as engineers with an interest in information fusion, aerospace applications, radar data processing and remote sensing.

Author : Patricia Melin,Oscar Castillo,Janusz Kacprzyk
Publisher : Springer
Page : 838 pages
File Size : 43,5 Mb
Release : 2016-12-08
Category : Technology & Engineering
ISBN : 9783319470542

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Nature-Inspired Design of Hybrid Intelligent Systems by Patricia Melin,Oscar Castillo,Janusz Kacprzyk Pdf

This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book’s third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

Author : Ulrich Ramacher,Ulrich Rückert
Publisher : Springer Science & Business Media
Page : 346 pages
File Size : 44,5 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461539940

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VLSI Design of Neural Networks by Ulrich Ramacher,Ulrich Rückert Pdf

The early era of neural network hardware design (starting at 1985) was mainly technology driven. Designers used almost exclusively analog signal processing concepts for the recall mode. Learning was deemed not to cause a problem because the number of implementable synapses was still so low that the determination of weights and thresholds could be left to conventional computers. Instead, designers tried to directly map neural parallelity into hardware. The architectural concepts were accordingly simple and produced the so called interconnection problem which, in turn, made many engineers believe it could be solved by optical implementation in adequate fashion only. Furthermore, the inherent fault-tolerance and limited computation accuracy of neural networks were claimed to justify that little effort is to be spend on careful design, but most effort be put on technology issues. As a result, it was almost impossible to predict whether an electronic neural network would function in the way it was simulated to do. This limited the use of the first neuro-chips for further experimentation, not to mention that real-world applications called for much more synapses than could be implemented on a single chip at that time. Meanwhile matters have matured. It is recognized that isolated definition of the effort of analog multiplication, for instance, would be just as inappropriate on the part ofthe chip designer as determination of the weights by simulation, without allowing for the computing accuracy that can be achieved, on the part of the user.

Author : Srikanta Patnaik,Xin-She Yang,Ishwar K. Sethi
Publisher : Springer Nature
Page : 853 pages
File Size : 42,6 Mb
Release : 2020-07-25
Category : Technology & Engineering
ISBN : 9789811552434

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Advances in Machine Learning and Computational Intelligence by Srikanta Patnaik,Xin-She Yang,Ishwar K. Sethi Pdf

This book gathers selected high-quality papers presented at the International Conference on Machine Learning and Computational Intelligence (ICMLCI-2019), jointly organized by Kunming University of Science and Technology and the Interscience Research Network, Bhubaneswar, India, from April 6 to 7, 2019. Addressing virtually all aspects of intelligent systems, soft computing and machine learning, the topics covered include: prediction; data mining; information retrieval; game playing; robotics; learning methods; pattern visualization; automated knowledge acquisition; fuzzy, stochastic and probabilistic computing; neural computing; big data; social networks and applications of soft computing in various areas.

Author : Yi Sun,Huchuan Lu,Lihe Zhang,Jian Yang,Hua Huang
Publisher : Springer
Page : 0 pages
File Size : 45,5 Mb
Release : 2017-09-14
Category : Computers
ISBN : 3319677764

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Intelligence Science and Big Data Engineering by Yi Sun,Huchuan Lu,Lihe Zhang,Jian Yang,Hua Huang Pdf

This book constitutes the proceedings of the 7th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2017, held in Dalian, China, in September 2017.The 48 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 121 submissions. They deal with statistics and learning; deep neural networks; faces and people; objects; classification and clustering; imaging; biomedical signal processing; and recommendation.

Author : Roumen Kountchev,Rumen Mironov,Shengqing Li
Publisher : Springer Nature
Page : 268 pages
File Size : 43,5 Mb
Release : 2021-04-20
Category : Technology & Engineering
ISBN : 9789813346765

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New Approaches for Multidimensional Signal Processing by Roumen Kountchev,Rumen Mironov,Shengqing Li Pdf

This book is a collection of papers presented at the International Workshop on New Approaches for Multidimensional Signal Processing (NAMSP 2020), held at Technical University of Sofia, Sofia, Bulgaria, during 09–11 July 2020. The book covers research papers in the field of N-dimensional multicomponent image processing, multidimensional image representation and super-resolution, 3D image processing and reconstruction, MD computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge data mining, watermarking, hiding and encryption of MD images, MD image processing in robot systems, tensor-based data processing, 3D and multi-view visualization, forensic analysis systems for MD images and many more.

Author : Thangaprakash Sengodan,M. Murugappan,Sanjay Misra
Publisher : Springer Nature
Page : 1335 pages
File Size : 48,6 Mb
Release : 2021-02-26
Category : Technology & Engineering
ISBN : 9789811590191

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Advances in Electrical and Computer Technologies by Thangaprakash Sengodan,M. Murugappan,Sanjay Misra Pdf

This book comprises select proceedings of the International Conference on Advances in Electrical and Computer Technologies 2020 (ICAECT 2020). The papers presented in this book are peer-reviewed and cover latest research in electrical, electronics, communication and computer engineering. Topics covered include smart grids, soft computing techniques in power systems, smart energy management systems, power electronics, feedback control systems, biomedical engineering, geo informative systems, grid computing, data mining, image and signal processing, video processing, computer vision, pattern recognition, cloud computing, pervasive computing, intelligent systems, artificial intelligence, neural network and fuzzy logic, broad band communication, mobile and optical communication, network security, VLSI, embedded systems, optical networks and wireless communication. The volume can be useful for students and researchers working in the different overlapping areas of electrical, electronics and communication engineering.

Author : Charu C. Aggarwal
Publisher : Springer
Page : 497 pages
File Size : 53,6 Mb
Release : 2018-08-25
Category : Computers
ISBN : 9783319944630

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Neural Networks and Deep Learning by Charu C. Aggarwal Pdf

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.