Cellular Simultanous Recurrent Networks For Image Processing PDF Download
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Author | : John Keith Anderson |
Publisher | : |
Total Pages | : |
Release | : 2013 |
Genre | : |
ISBN | : |
Download Cellular Simultanous Recurrent Networks for Image Processing Book in PDF, ePub and Kindle
Artificial neural networks are inspired by the abilities of humans and animals to learn and adapt. Feed-forward networks are both fast and powerful, and are particularly useful for statistical pattern recognition. These networks are inspired by portions of the brain such as the visual cortex. However, feed-forward networks have been shown inadequate for complex applications such as long-term optimization, reinforced learning and image processing. Cellular Neural Networks (CNNs) are a type of recurrent network which have been used extensively for image processing. CNNs have shown limited success solving problems which involve topological relationships. Such problems include geometric transformations such as affine transformation and image registration. The Cellular Simultaneous Recurrent Network (CSRN) has been exploited to solve the 2D maze traversal problem, which is a long-term optimization problem with similar topological relations. From its inception, it has been speculated that the CSRN may have important implications in image processing. However, to date, very little work has been done to study CSRNs for image processing tasks. In this work, we investigate CSRNs for image processing. We propose a novel, generalized architecture for the CSRN suitable for generic image processing tasks. This architecture includes the use of sub-image processing which greatly improves the efficacy of CSRNs for image processing. We demonstrate the application of the CSRN with this generalized architecture across a variety of image processing problems including pixel level transformations, filtering, and geometric transformations. Results are evaluated and compared with standard MATLAB® functions. To better understand the inner workings of the CSRN we investigate the use of various CSRN cores including: 1) the original Generalized Multi-Layered Perceptron (GMLP) core used by Pang and Werbos to solve the 2D maze traversal problem, 2) the Elman Simultaneous Recurrent Network (ESRN), and 3) a novel ESRN core with multi-layered feedback. We compare the functionality of these cores in image processing applications. Further, we introduce the application of the unscented Kalman filter (UKF) for training of the CSRN. Results are compared with the standard Extended Kalman Filter (EKF) training method of CSRN. Finally, implications of current findings and proposed research directions are presented.
Author | : Teddy Salan |
Publisher | : |
Total Pages | : |
Release | : 2011 |
Genre | : |
ISBN | : |
Download A Dynamic Approach to Pose Invariant Face Identification Using Cellular Simultaneous Recurrent Networks Book in PDF, ePub and Kindle
Face recognition is a widely covered and desirable research field that produced multiple techniques and different approaches. Most of them have severe limitations with pose variations or face rotation. The immediate goal of this thesis is to deal with pose variations by implementing a face recognition system using a Cellular Simultaneous Recurrent Network (CSRN). The CSRN is a novel bio-inspired recurrent neural network that mimics reinforcement learning in the brain. The recognition task is defined as an identification problem on image sequences. The goal is to correctly match a set of unknown pose distorted probe face sequences with a set of known gallery sequences. This system comprises of a pre-processing stage for face and feature extraction and a recognition stage to perform the identification. The face detection algorithm is based on the scale-space method combined with facial structural knowledge. These steps include extraction of key landmark points and motion unit vectors that describe movement of face sequqnces. The identification process applies Eigenface and PCA and reduces each image to a pattern vector used as input for the CSRN. In the training phase the CSRN learns the temporal information contained in image sequences. In the testing phase the network predicts the output pattern and finds similarity with a test input pattern indicating a match or mismatch.Previous applications of a CSRN system in face recognition have shown promise. The first objective of this research is to evaluate those prior implementations of CSRN-based pose invariant face recognition in video images with large scale databases. The publicly available VidTIMIT Audio-Video face dataset provides all the sequences needed for this study. The second objective is to modify a few well know standard face recognition algorithms to handle pose invariant face recognition for appropriate benchmarking with the CSRN. The final objective is to further improve CSRN face recognition by introducing motion units which can be used to capture the direction and intensity of movement of feature points in a rotating face.
Author | : Ronald Tetzlaff |
Publisher | : World Scientific |
Total Pages | : 700 |
Release | : 2002 |
Genre | : Technology & Engineering |
ISBN | : 981238121X |
Download Cellular Neural Networks and Their Applications Book in PDF, ePub and Kindle
This volume covers the fundamental theory of Cellular Neural Networks as well as their applications in various fields such as science and technology. It contains all 83 papers of the 7th International Workshop on Cellular Neural Networks and their Applications. The workshop follows a biennial series of six workshops consecutively hosted in Budapest (1990), Munich, Rome, Seville, London and Catania (2000).
Author | : Jennie Si |
Publisher | : John Wiley & Sons |
Total Pages | : 670 |
Release | : 2004-08-02 |
Genre | : Technology & Engineering |
ISBN | : 9780471660545 |
Download Handbook of Learning and Approximate Dynamic Programming Book in PDF, ePub and Kindle
A complete resource to Approximate Dynamic Programming (ADP), including on-line simulation code Provides a tutorial that readers can use to start implementing the learning algorithms provided in the book Includes ideas, directions, and recent results on current research issues and addresses applications where ADP has been successfully implemented The contributors are leading researchers in the field
Author | : Pradeep Kumar Mallick |
Publisher | : Springer Nature |
Total Pages | : 961 |
Release | : 2021-07-01 |
Genre | : Technology & Engineering |
ISBN | : 9811610568 |
Download Cognitive Informatics and Soft Computing Book in PDF, ePub and Kindle
This book presents best selected research papers presented at the 3rd International Conference on Cognitive Informatics and Soft Computing (CISC 2020), held at Balasore College of Engineering & Technology, Balasore, Odisha, India, from 12 to 13 December 2020. It highlights, in particular, innovative research in the fields of cognitive informatics, cognitive computing, computational intelligence, advanced computing, and hybrid intelligent models and applications. New algorithms and methods in a variety of fields are presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of computer science, artificial intelligence, cybernetics, automation control theory, and software engineering.
Author | : Radu Matei |
Publisher | : |
Total Pages | : |
Release | : 2009 |
Genre | : |
ISBN | : 9789533070094 |
Download New Model and Applications of Cellular Neural Networks in Image Processing Book in PDF, ePub and Kindle
Author | : Igor Aizenberg |
Publisher | : Springer Science & Business Media |
Total Pages | : 274 |
Release | : 2013-03-14 |
Genre | : Science |
ISBN | : 1475731159 |
Download Multi-Valued and Universal Binary Neurons Book in PDF, ePub and Kindle
Multi-Valued and Universal Binary Neurons deals with two new types of neurons: multi-valued neurons and universal binary neurons. These neurons are based on complex number arithmetic and are hence much more powerful than the typical neurons used in artificial neural networks. Therefore, networks with such neurons exhibit a broad functionality. They can not only realise threshold input/output maps but can also implement any arbitrary Boolean function. Two learning methods are presented whereby these networks can be trained easily. The broad applicability of these networks is proven by several case studies in different fields of application: image processing, edge detection, image enhancement, super resolution, pattern recognition, face recognition, and prediction. The book is hence partitioned into three almost equally sized parts: a mathematical study of the unique features of these new neurons, learning of networks of such neurons, and application of such neural networks. Most of this work was developed by the first two authors over a period of more than 10 years and was only available in the Russian literature. With this book we present the first comprehensive treatment of this important class of neural networks in the open Western literature. Multi-Valued and Universal Binary Neurons is intended for anyone with a scholarly interest in neural network theory, applications and learning. It will also be of interest to researchers and practitioners in the fields of image processing, pattern recognition, control and robotics.
Author | : Tao Yang |
Publisher | : |
Total Pages | : 376 |
Release | : 2002 |
Genre | : Computers |
ISBN | : |
Download Cellular Neural Networks and Image Processing Book in PDF, ePub and Kindle
Yang, who is not identified, applies the design principles of cellular image operators to a hardware platform called cellular neural network (CNN), a VLSI-oriented vision chip invented in 1988. Having presented different local rules in previous works, he here examines many local rule classes that can be implemented by a CNN, exploiting such unique characteristics as its ability to process three source images in parallel and so define computations among the three. The study is second in his trilogy on cellular image processing algorithms and cellular hardware platforms. Annotation copyrighted by Book News, Inc., Portland, OR.
Author | : |
Publisher | : |
Total Pages | : 202 |
Release | : 2001 |
Genre | : Image processing |
ISBN | : |
Download Applications of Artificial Neural Networks in Image Processing Book in PDF, ePub and Kindle
Author | : Wei Qi Yan |
Publisher | : Springer |
Total Pages | : 222 |
Release | : 2019-02-21 |
Genre | : Computers |
ISBN | : 3030107132 |
Download Introduction to Intelligent Surveillance Book in PDF, ePub and Kindle
This practically-oriented textbook introduces the fundamentals of designing digital surveillance systems powered by intelligent computing techniques. The text offers comprehensive coverage of each aspect of the system, from camera calibration and data capture, to the secure transmission of surveillance data, in addition to the detection and recognition of individual biometric features and objects. The coverage concludes with the development of a complete system for the automated observation of the full lifecycle of a surveillance event, enhanced by the use of artificial intelligence and supercomputing technology. This updated third edition presents an expanded focus on human behavior analysis and privacy preservation, as well as deep learning methods. Topics and features: contains review questions and exercises in every chapter, together with a glossary; describes the essentials of implementing an intelligent surveillance system and analyzing surveillance data, including a range of biometric characteristics; examines the importance of network security and digital forensics in the communication of surveillance data, as well as issues of issues of privacy and ethics; discusses the Viola-Jones object detection method, and the HOG algorithm for pedestrian and human behavior recognition; reviews the use of artificial intelligence for automated monitoring of surveillance events, and decision-making approaches to determine the need for human intervention; presents a case study on a system that triggers an alarm when a vehicle fails to stop at a red light, and identifies the vehicle’s license plate number; investigates the use of cutting-edge supercomputing technologies for digital surveillance, such as FPGA, GPU and parallel computing. This concise and accessible work serves as a classroom-tested textbook for graduate-level courses on intelligent surveillance. Researchers and engineers interested in entering this area will also find the book suitable as a helpful self-study reference.