artificial neural networks pattern (164 Ergebnisse)

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 286 | Sprache: Englisch | Produktart: Bücher.

Softcover. Zustand: Bon. Ancien livre de bibliothèque. Traces d'usure sur la couverture. Petite(s) trace(s) de pliure sur la couverture. Edition 1991. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Signs of wear on the cover. Slightly creased cover. Edition 1991. Ammareal gives back up to 15% of this item's net price to charity organizations.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 288 | Sprache: Englisch | Produktart: Bücher.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 5th INNS IAPR TC3 GIRPR International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2012, held in Trento, Italy, in September 2012. The 21 revised full papers presented were carefully reviewed and selected for inclusion in this volume. They cover a large range of topics in the field of neural network- and machine learning-based pattern recognition presenting and discussing the latest research, results, and ideas in these areas.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the Second IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2006, held in Ulm, Germany in August/September 2006. The 26 revised papers presented were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on unsupervised learning, semi-supervised learning, supervised learning, support vector learning, multiple classifier systems, visual object recognition, and data mining in bioinformatics. 316 pp. Englisch.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.

paperback. Zustand: Very Good.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic.The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the 10th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2022, held in Dubai, UAE, in November 2022. The 16 revised full papers presented were carefully reviewed and selected from 24 submissions. The conference presents papers on subject such as pattern recognition and machine learning based on artificial neural networks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 216 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -This book constitutes the refereed proceedings of the 7th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2016, held in Ulm, Germany, in September 2016.The 25 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 32 submissions for inclusion in this volume. The workshop will act as a major forum for international researchers and practitioners working in all areas of neural network- and machine learning-based pattern recognition to present and discuss the latest research, results, and ideas in these areas.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 348 pp. Englisch.

Soft cover. Zustand: As New. 8vo (22.5 cm), XIV, 271 pp. Laminated wrappers. The book explores the intriguing interplay between two prominent fields in the realm of machine learning and data analysis. This thought-provoking book delves into the historical development and the modern-day synergies between artificial neural networks (ANNs) and statistical pattern recognition (SPR), shedding light on their shared roots and divergent paths. By examining the historical context, readers gain a comprehensive understanding of how ANNs and SPR have evolved independently over time. The book traces their origins, from the early perceptron models and foundational statistical techniques to the emergence of deep learning and advanced probabilistic models. Through this historical lens, it becomes evident that ANNs and SPR have followed distinct trajectories, with ANNs prioritizing flexible, connectionist approaches, and SPR emphasizing probabilistic modeling and statistical inference. However, the book goes beyond mere historical analysis and illuminates the contemporary convergence of ANNs and SPR. It explores how recent developments in both fields have led to a remarkable convergence, creating new avenues for collaboration and synergy. The advent of deep learning, which combines ANN architectures with large-scale data and computational power, has revolutionized both ANNs and SPR, unlocking new possibilities for pattern recognition, data analysis, and decision-making.

Taschenbuch. Zustand: Neu. Neuware Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 420 pp. Englisch.

Zustand: New.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a study based on the concepts and artificial neural architectures and their applications in general, and specifically pattern recognition. The Borland Delphi 7 platform and programming language is used to implement two systems, one for image recognition and the other for sound recognition. The Borland Delphi programming language uses some components that simulate the architecture and concepts of MLP (multilayer perceptron) and SOM (Self Organizing Map) networks.In order to work with both types of pattern recognition, we use two independently programmed applications with two different artificial neural networks, one that performs image recognition, and the other that performs sound recognition. We use character type images for the image recognition network, in the application in question we specifically use images of digits. And the sound recognition network uses the concept of sound tones for recognition, so it will be specifically recognized sound tones idealizing the reproduction of the sound of a telephone keypad.

Hardcover. Zustand: Very Good. Very Good. book.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The use of hematological analyzers has become routine in clinical practice, but the sheer volume of data produced by these devices often makes manual inspection of all the results an unwieldy task. For this reason, automated pattern analysis through the use of machine learning has been used in these types of situations, to save time and to provide invaluable aid to medical professionals in this area of diagnostic medicine. Toward this end, Artificial Neural Networks (ANNs) are often relied upon in the field of machine learning, because of their ability to distill representative feature components from large amounts of input data. This paper details an approach in which the scatterplots of cells that were produced by a hematological device were used as inputs. The data were separated into two classes, one containing clinically Normal samples, and the second containing abnormal samples that contained Variant Lymphocytes. Statistical features were extracted from these data using Principal Component Analysis (PCA) and then a Perceptron ANN was employed to differentiate between the two classes of data. The accuracy of pattern classification using this method was then discussed.

Paperback. Zustand: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock. This item is printed on demand.