Deep Learning & Neuronale Netze – alle Bücher

Deep Ray, Orazio Pinti, Assad A. Oberai
Deep Learning and Computational Physics

The main objective of this book is to introduce a student who is familiar with elementary math concepts to select topics in deep learning. It exploits strong connections between deep learning algorithms a…

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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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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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Distributed Deep Learning and Explainable AI (XAI) in Industry 4.0

This book is a comprehensive resource that delves into the integration of advanced artificial intelligence techniques within the context of modern industrial practices. It systematically explores how dist…

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

Introduction.- Introduction to Human Activity Recognition, Fall Monitoring and Detection, Health monitoring.- Fundamental concepts.- Machine Learning in Human Activity Recognition using Smartphone Sensors…

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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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Proceedings of the International Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication

This book is a collection of best selected research papers presented at the 2nd Conference on Machine Learning, Deep Learning and Computational Intelligence for Wireless Communication (MDCWC 2023) held du…

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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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Deep Learning Theory and Applications

Communications in Computer and Information Science - Band 2627

.- End-to-End ASR Model with Iterative Attention Mechanism Enhanced RNN Model for Phoneme Recognition..- Diagnostic Trouble Codes Prediction with DTC-GOAT and Ensembles..- A Fast Fourier Transform-Aided D…

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Kwang Hun Kim, Ju Song Kim, Song Il Ri
Application of data decomposition and deep learning technique

Water pollution is one of the most serious environmental problems worldwide. Accurate forecast of water quality is of great importance since it can provide useful information for the managers to minimize …

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Carsten Holst
Automated Flank Wear Segmentation and Measurement with Deep Learning Image Processing

This thesis optimizes AI models for identifying tool wear on microscopic images of cutting tools. It creates a tool wear model from empirical trials to generate a dataset and conducts screening analysis t…

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Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis

Emerging Trends and Applications of Deep Learning for Biomedical Data Analysis introduces the latest emerging trends and applications of deep learning in biomedical data analysis. This book delves into va…

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Patrick Klein
Combining Expert Knowledge and Deep Learning with Case-Based Reasoning for Predictive Maintenance

If a manufacturing company's main goal is to sell products profitably, protecting production systems from defects is essential and has led to vast documentation and expert knowledge. Industry 4.0 has faci…

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Harvey B. Mitchell
Data Fusion

1 Introduction.- 2 Sensors.- 3 Architecture.- 4 Common Representational Format.- 5 Deep Learning.- 6 Spatial Alignment.- 7 Temporal Alignment.- 8 Semantic Alignment.- 9 Radiometric Normalization.- 10 Baye…

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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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Joachim Steinwendner, Roland Schwaiger
Programming Neural Networks with Python

Neural networks are at the heart of AI-so ensure you're on the cutting edge with this guide! For true beginners, get a crash course in Python and the mathematical concepts you'll need to understand and cr…

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Chisom Nwokwu
Data Engineering for Beginners

A hands-on technical and industry roadmap for aspiring data engineersIn Data Engineering for Beginners, big data expert Chisom Nwokwu delivers a beginner-friendly handbook for everyone interested in the f…

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Luca Antiga, Eli Stevens, Howard Huang, Thomas Viehmann
Deep Learning with Pytorch, Second Edition

Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.PyTorch …

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Juliane Blarr
Development of Computational, Image Processing and Deep Learning Methods for the Microstructure Characterization of Carbon Fiber Reinforced Polyamide 6 Based on CT Images

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 distri…

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Mohammad Nauman
Keras 3

Harness the power of AI with this guide to using Keras! Start by reviewing the fundamentals of deep learning and installing the Keras API. Next, follow Python code examples to build your own models, and t…

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