Computational methods deep learning (95 resultados)

Condición: New. In English.

Condición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Condición: New. In English.

Condición: New.

Condición: New.

Condición: New.

Condición: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

Condición: New.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Discontinuously fiber reinforced polymers exhibit complex microstructures. Quantities to characterize the latter have been developed over time, such as the fiber volume content or fiber orientation distributions, which can be acquired through computed tomography images and subsequent image processing. This thesis deals with the development of (partially AI-based) methods in this context, especially considering challenges of contrast and resolution with carbon fibers and scale-bridging issues.…

Condición: New.

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.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: New.

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.

Condición: New.

Condición: New.

Condición: New.

Condición: New.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical models, and algorithmic implementation, as well as covers datasets preparation, programming, results analysis and evaluations.Beginning with a grounding about artificial neural networks with neurons and the activation functions, the work then explains the mechanism of deep learning using advanced mathematics. In particular, it emphasizes how to use TensorFlow and the latest MATLAB deep-learning toolboxes for implementing deep learning algorithms.As a prerequisite, readers should have a solid understanding especially of mathematical analysis, linear algebra, numerical analysis, optimizations, differential geometry, manifold, and information theory, as well as basic algebra, functional analysis, and graphical models. This computational knowledge will assist in comprehending the subject matter not only of this text/reference, but also in relevant deep learning journal articles and conference papers.This textbook/guide is aimed at Computer Science research students and engineers, as well as scientists interested in deep learning for theoretic research and analysis. More generally, this book is also helpful for those researchers who are interested in machine intelligence, pattern analysis, natural language processing, and machine vision.Dr. Wei Qi Yanis an Associate Professor in the Department of Computer Science at Auckland University of Technology, New Zealand. His other publications include the Springer title,Visual Cryptography for Image Processing and Security.…

Condición: As New. Unread book in perfect condition.

Condición: New.

Taschenbuch. Condición: Neu. Development of Computational, Image Processing and Deep Learning Methods for the Microstructure Characterization of Carbon Fiber Reinforced Polyamide 6 Based on CT Images | Juliane Blarr | Taschenbuch | Englisch | 2025 | Karlsruher Institut für Technologie | EAN 9783731513964 | Verantwortliche Person für die EU: KIT Scientific Publishing, Straße am Forum 2, 76131 Karlsruhe, info[at]ksp[dot]kit[dot]edu | Anbieter: preigu.…

Condición: New. In English.

Condición: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Condición: As New. Unread book in perfect condition.

Condición: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently updated this book.The second edition of this textbook presents control theory, transformer models, and graph neural networks (GNN) in deep learning. We have incorporated the latest algorithmic advances and large-scale deep learning models, such as GPTs, to align with the current research trends. Through the second edition, this book showcases how computational methods in deep learning serve as a dynamic driving force in this era of artificial intelligence (AI). This book is intended for research students, engineers, as well as computer scientists with interest in computational methods in deep learning. Furthermore, it is also well-suited for researchers exploring topics such as machine intelligence, robotic control, and related areas.…

Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.