Deep Learning & Neuronale Netze – alle Bücher

Deep Learning and Visual Artificial Intelligence

This book features high-quality research papers presented at the International Conference on Deep Learning and Visual Artificial Intelligence (ICDLAI), held at Government Engineering College Bikaner, Bika…

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Machine Learning, Deep Learning and AI for Cybersecurity

This book addresses a variety of problems that arise at the interface between AI techniques and challenging problems in cybersecurity. The book covers many of the issues that arise when applying AI and de…

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Machine Learning and Deep Learning in Drug Design

Machine learning (ML) and deep learning (DL) are reshaping the landscape of drug design. This comprehensive volume explores how these technologies are applied across the entire drug discovery pipeline--fr…

lieferbar ab 22.7.2026.

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Ravikumar Kurup, Parameswara Achutha Kurup
Die Leere und der quantenklassische Zustand - Störung des kosmischen neuronalen Netzes

Stellare Galaxien und Planeten sind biologischen Ursprungs und arbeiten bewusst als organische Quantencomputer, die auf bewussten Quantenfeldern aufgebaut sind. Sie bestehen aus symbiotischen Netzwerken v…

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Suparna Biswas
Machine Learning and Deep Learning in Human Activity Recognition and Fall Detection

Signals and Communication Technology

This book presents research into the domain of Human Activity Recognition (HAR) and Fall Detection (FD), with a focus on the seamless monitoring and support of elderly people. The author shows how current…

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Mathias Dehn
Korrektur des thermo-elastischen Maschinenfehlers von Fräsmaschinen mithilfe von künstlichen neuronalen Netzen und maschineninternen Daten

Thermo-elastische Fehler zählen zu den Hauptursachen für Ungenauigkeiten an Fräsmaschinen. Diese Dissertation präsentiert ein innovatives Korrekturmodell auf Basis Künstlicher Neuronaler Netze, das vollst…

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Jonathan Pukas
Werknutzung und künstliche Intelligenz

Datenrecht und neue Technologien - Band 14

Diese Arbeit analysiert, welche Rahmenbedingungen das Urheberrecht für die Verwendung von Werken als Trainings- und Inputdaten künstlicher neuronaler Netze zur Verfügung stellt. Sie liefert damit Antworte…

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Alberto Bressan, Alfio Quarteroni, Guido De Philippis, Leon Bungert
PDEs, Control and Deep Learning

Lecture Notes in Mathematics

This volume includes lectures presented at the CIME School on "PDEs, Control and Deep Learning", held in Cetraro (Italy) from July 22 to 26, 2024. It provides a comprehensive and up-to-date view…

lieferbar ab 6.9.2026.

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Deep Learning Theory and Applications

Communications in Computer and Information Science - Band 2627

This book constitutes revised selected papers from the 6th International Conference on Deep Learning Theory and Applications, DeLTA 2025, which took place in Bilbao, Spain, during June 12-13, 2025.The 9 f…

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Shirui Wang, Wenyi Hu, Xuqing Wu, Jiefu Chen
Deep Learning for Seismic Data Enhancement and Representation

Advances in Oil and Gas Exploration & Production

Seismic imaging is a key component of subsurface exploration, and it depends on a high-quality seismic data acquisition system with effective seismic processing algorithms. Seismic data quality concerns v…

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Wei Cai
Deterministic, Stochastic, and Deep Learning Methods for Computational Electromagnetics

This book provides a well-balanced and comprehensive picture based on clear physics, solid mathematical formulation, and state-of-the-art useful numerical methods in deterministic, stochastic, deep neural…

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Novel Deep Learning Methodologies in Industrial and Applied Mathematics

ICIAM2023 Springer Series - Band 9

This book presents a collection of research papers exploring innovative applications of Artificial Intelligence (AI) in Industrial and Applied Mathematics (IAM). It begins with an introduction to the know…

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Carlos Urdaneta, Aamir Bader Shah, Xuqing Wu, Xin Fu
Deep Learning Applications for Drilling Performance: Forecasting, Diagnostics, Telemetry, and Predictive Maintenance

Advances in Oil and Gas Exploration & Production

This book presents data driven approaches to improve drilling performance in geothermal, coiled tubing, and conventional operations. It begins with transformer models for forecasting rate of penetration i…

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Yi He
InSAR and Deep Learning in Landslides Research: Intelligent Identification, Risk Assessment and Susceptibility Mapping

This book combines remote sensing and deep learning technology to develop a variety of models in the study of different type landslides in a wide range of areas including northwest, southwest and southern…

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Sen Lin, Zhi Zhou, Zhaofeng Zhang, Xu Chen
Edge Intelligence in the Making

Synthesis Lectures on Learning, Networks, and Algorithms

This book conducts a comprehensive and detailed survey of the recent research efforts in edge intelligence. The authors first review the background and present motivation for AI running at the network edg…

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Harvey B. Mitchell
Data Fusion

This textbook provides a comprehensive introduction to the concepts and ideas of data fusion. It is an extensively revised third edition of the author's book which was originally published by Springer-Ver…

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Fato& Yarman Vural, Mo&, Ertu&
Image Processing

Richly supplemented one-semester textbook on intermediate/advanced image processingImage Processing with Pythonintroduces a novel approach to image processing methods, combining the foundational and deep …

lieferbar ab 17.9.2026.

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Barouch Matzliach, Eugene Kagan, Irad Ben-Gal
Multi-Agent Search under Uncertainty

Plan optimal multi-robot search paths despite imperfect sensor informationWhen multiple robots must locate targets in presence of false positive and false negative detection errors, path planning becomes …

lieferbar ab 29.10.2026.

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Artificial Intelligence for Global Counter-Terrorism

Contributions to Security and Defence Studies

The emergence of global terrorism has led to new, innovative artificial intelligence (AI) and deep learning techniques for effective counterterrorism. This book explores the transformative role of AI and …

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Akihiko Takahashi, Toshihiro Yamada
Asymptotic Expansion and Weak Approximation

SpringerBriefs in Statistics

This book provides a self-contained lecture on a Malliavin calculus approach to asymptotic expansion and weak approximation of stochastic differential equations (SDEs), along with numerical methods for co…

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