artificial neural networks pattern (169 resultados)

Condición: Very Good. *Price HAS BEEN reduced by 10% until Monday, Aug. 18 (weekend SALE item)* 224 pp., Paperback, very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

Hardcover. Condición: Très bon. Ancien livre de bibliothèque. Couverture différente. Edition 1991. Tome 11. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Different cover. Edition 1991. Volume 11. Ammareal gives back up to 15% of this item's net price to charity organizations.

Condición: 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.

paperback. Condición: Fine.

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

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Taschenbuch. Condición: 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.

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Paperback. Condición: Brand New. 286 pages. 9.00x6.00x0.65 inches. In Stock.

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Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Novel Approaches to Training Artificial Neural Networks for Pattern Recognition presents a cutting-edge examination of the latest advancements in training artificial neural networks for pattern recognition tasks. This book explores the application of innovative algorithms, architectures, and techniques to enhance the performance and efficiency of neural networks in recognizing complex patterns. By examining the theoretical foundations and practical implementations of these novel approaches, the book provides a comprehensive understanding of the potential applications of neural networks in fields such as computer vision, natural language processing, and predictive analytics. From the development of novel activation functions to the integration of transfer learning and ensemble methods, this book offers a detailed exploration of the latest trends and advancements in neural network training. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

paperback. Condición: New. New. book.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. In the realm of artificial intelligence, the quest for improved pattern recognition has led to the development of novel approaches to training neural networks. This book explores the cutting-edge techniques that have revolutionized the field, from the application of transfer learning to the utilization of meta-heuristics. By examining the intricacies of neural network architecture and the role of hyperparameter tuning, readers will gain a deeper understanding of the complex interplay between model design and performance. The book also delves into the realm of deep learning, where convolutional neural networks and recurrent neural networks are employed to tackle a wide range of pattern recognition tasks. With its focus on the latest advancements and the most effective strategies, this book is an essential resource for researchers and practitioners seeking to push the boundaries of artificial intelligence. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. This book offers a fascinating exploration of the parallels between human memory and pattern formation in artificial neural networks. By examining the ways in which neural networks learn and adapt, the author reveals the intricate mechanisms underlying memory formation and retrieval. Through a series of theoretical analyses and computational simulations, 'Memory and Pattern Formation in Artificial Neural Networks' provides a richly detailed understanding of the complex relationships between memory, cognition, and computation. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Memory and Pattern Formation in Artificial Neural Networks examines the mechanisms by which artificial systems emulate human memory processes and pattern recognition. The book details the architecture of neural networks designed for learning and memory storage, highlighting how these models can replicate complex cognitive functions. It discusses the algorithms that enable pattern formation and the implications for artificial intelligence development. This comprehensive analysis bridges neuroscience and computer science, illustrating how artificial neural networks can serve as models for understanding biological memory systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

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