Dynamic Neural Field Theory For Motion Perception

Author: Martin A. Giese
Publisher: Springer Science & Business Media
ISBN: 1461555817
Size: 45.32 MB
Format: PDF, ePub
View: 399
Download
Dynamic Neural Field Theory for Motion Perception provides a new theoretical framework that permits a systematic analysis of the dynamic properties of motion perception. This framework uses dynamic neural fields as a key mathematical concept. The author demonstrates how neural fields can be applied for the analysis of perceptual phenomena and its underlying neural processes. Also, similar principles form a basis for the design of computer vision systems as well as the design of artificially behaving systems. The book discusses in detail the application of this theoretical approach to motion perception and will be of great interest to researchers in vision science, psychophysics, and biological visual systems.

Hierarchical Neural Networks For Image Interpretation

Author: Sven Behnke
Publisher: Springer
ISBN: 3540451692
Size: 79.99 MB
Format: PDF, Kindle
View: 4270
Download
Human performance in visual perception by far exceeds the performance of contemporary computer vision systems. While humans are able to perceive their environment almost instantly and reliably under a wide range of conditions, computer vision systems work well only under controlled conditions in limited domains. This book sets out to reproduce the robustness and speed of human perception by proposing a hierarchical neural network architecture for iterative image interpretation. The proposed architecture can be trained using unsupervised and supervised learning techniques. Applications of the proposed architecture are illustrated using small networks. Furthermore, several larger networks were trained to perform various nontrivial computer vision tasks.

From Animals To Animats 13

Author: Angel P. del Pobil
Publisher: Springer
ISBN: 3319088645
Size: 47.31 MB
Format: PDF, Kindle
View: 6819
Download
This book constitutes the proceedings of the 13th International Conference on Simulation of Adaptive Behavior, SAB 2014, held in Castellón, Spain, in July 2014. The 32 papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. They cover the main areas in animat research, including the animat approach and methodology, perception and motor control, navigation and internal world models, learning and adaptation, evolution and collective and social behavior.

Computer Vision

Author: Richard Szeliski
Publisher: Springer
ISBN: 9781848829466
Size: 70.82 MB
Format: PDF, Docs
View: 5661
Download
Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.

Neural Fields

Author: Stephen Coombes
Publisher: Springer
ISBN: 3642545939
Size: 48.76 MB
Format: PDF, Kindle
View: 1666
Download
Neural field theory has a long-standing tradition in the mathematical and computational neurosciences. Beginning almost 50 years ago with seminal work by Griffiths and culminating in the 1970ties with the models of Wilson and Cowan, Nunez and Amari, this important research area experienced a renaissance during the 1990ties by the groups of Ermentrout, Robinson, Bressloff, Wright and Haken. Since then, much progress has been made in both, the development of mathematical and numerical techniques and in physiological refinement und understanding. In contrast to large-scale neural network models described by huge connectivity matrices that are computationally expensive in numerical simulations, neural field models described by connectivity kernels allow for analytical treatment by means of methods from functional analysis. Thus, a number of rigorous results on the existence of bump and wave solutions or on inverse kernel construction problems are nowadays available. Moreover, neural fields provide an important interface for the coupling of neural activity to experimentally observable data, such as the electroencephalogram (EEG) or functional magnetic resonance imaging (fMRI). And finally, neural fields over rather abstract feature spaces, also called dynamic fields, found successful applications in the cognitive sciences and in robotics. Up to now, research results in neural field theory have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. There is no comprehensive collection of results or reviews available yet. With our proposed book Neural Field Theory, we aim at filling this gap in the market. We received consent from some of the leading scientists in the field, who are willing to write contributions for the book, among them are two of the founding-fathers of neural field theory: Shun-ichi Amari and Jack Cowan.

Artificial Neural Networks And Machine Learning Icann 2017

Author: Alessandra Lintas
Publisher: Springer
ISBN: 3319686003
Size: 23.79 MB
Format: PDF
View: 2291
Download
The two volume set, LNCS 10613 and 10614, constitutes the proceedings of then 26th International Conference on Artificial Neural Networks, ICANN 2017, held in Alghero, Italy, in September 2017. The 128 full papers included in this volume were carefully reviewed and selected from 270 submissions. They were organized in topical sections named: From Perception to Action; From Neurons to Networks; Brain Imaging; Recurrent Neural Networks; Neuromorphic Hardware; Brain Topology and Dynamics; Neural Networks Meet Natural and Environmental Sciences; Convolutional Neural Networks; Games and Strategy; Representation and Classification; Clustering; Learning from Data Streams and Time Series; Image Processing and Medical Applications; Advances in Machine Learning. There are 63 short paper abstracts that are included in the back matter of the volume.

The Physics Of The Mind And Brain Disorders

Author: Ioan Opris
Publisher: Springer
ISBN: 3319296744
Size: 71.30 MB
Format: PDF, ePub, Docs
View: 2578
Download
This book covers recent advances in the understanding of brain structure, function and disorders based on the fundamental principles of physics. It covers a broad range of physical phenomena occurring in the brain circuits for perception, cognition, emotion and action, representing the building blocks of the mind. It provides novel insights into the devastating brain disorders of the mind such as schizophrenia, dementia, autism, aging or addictions, as well as into the new devices for brain repair. The book is aimed at basic researchers in the fields of neuroscience, physics, biophysics and clinicians in the fields of neurology, neurosurgery, psychology, psychiatry.

Advanced Computational And Communication Paradigms

Author: Siddhartha Bhattacharyya
Publisher: Springer
ISBN: 9811082375
Size: 54.53 MB
Format: PDF, Mobi
View: 6299
Download
The book titled Advanced Computational and Communication Paradigms: Proceedings of International Conference on ICACCP 2017, Volume 2 presents refereed high-quality papers of the First International Conference on Advanced Computational and Communication Paradigms (ICACCP 2017) organized by the Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, held from 8– 10 September 2017. ICACCP 2017 covers an advanced computational paradigms and communications technique which provides failsafe and robust solutions to the emerging problems faced by mankind. Technologists, scientists, industry professionals and research scholars from regional, national and international levels are invited to present their original unpublished work in this conference. There were about 550 technical paper submitted. Finally after peer review, 142 high-quality papers have been accepted and registered for oral presentation which held across 09 general sessions and 05 special sessions along with 04 keynote address and 06 invited talks. This volume comprises 77 accepted papers of ICACCP 2017.