Machine learning

Recent breakthroughs in AI have not only increased demand for AI products, they've also lowered the barriers to entry for those who want to build AI products.

The production control of flexible manufacturing systems is a relevant component that must go along with the requirements of being flexible in terms of new product variants, new machine skills and reaction to unforeseen events during runtime.

Artificial intelligence (AI) is a concept, whose meaning and perception has changed considerably over the last decades.

Multilayer neural networks based on multi-valued neurons (MLMVNs) have been proposed to combine the advantages of complex-valued neural networks with a plain derivative-free learning algorithm.

This book explores the combination of Reinforcement Learning and Quantum Computing in the light of complex attacker-defender scenarios.

Der größte Teil des Weltwissens ist in digital verfügbaren Texten beschrieben.

Dieses Lehrbuch bietet eine solide Einführung in das Gebiet der Künstlichen Intelligenz, ohne dabei Programmierkenntnisse vorauszusetzen.

Changsheng Hua proposes two approaches, an input/output recovery approach and a performance index-based approach for robustness and performance optimization of feedback control systems.

Die vorliegende Dissertation präsentiert ein Konzept zur Steigerung der Energieeffizienz im Karosseriebau um durchschnittlich 10-15%.

Dieses essential befasst sich mit Anwendungen des maschinellen Lernens in verschiedenen Bereichen der Naturwissenschaften.

Vladislav Golyanik proposes several new methods for dense non-rigid structure from motion (NRSfM) as well as alignment of point clouds.

Markus Kachele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers.

Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures.

Daten sind das neue Gold - und neuronale Netze haben bereits einigen Unternehmen geholfen, diesen Schatz auszugraben.

Explore the capabilities of machine learning and neural networks.

This book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding.

This book is for individuals with a scientific background who aspire to apply machine learning within various natural science disciplines-such as physics, chemistry, biology, medicine, psychology and many more.

TensorFlow ist Googles herausragendes Werkzeug für das maschinelle Lernen, und dieses Buch macht es zugänglich, selbst wenn Sie bisher wenig über neuronale Netze und Deep Learning wissen.

This book presents an essential survey of the state of the art in the application of diverse computational methods to the interpretation, prediction, and design of high-performance battery materials.

This book explores the use of advanced geospatial techniques in geomorphic hazards modelling and risk reduction.

This book presents a new way of thinking about quantum mechanics and machine learning by merging the two.

This book presents a new way of thinking about quantum mechanics and machine learning by merging the two.

This book explores cutting-edge medical imaging advancements and their applications in clinical decision-making.

Be a part of the Tiny Machine Learning (TinyML) revolution in the ever-growing world of IoT.

This book explains the field of Generative Artificial Intelligence (AI), focusing on its potential and applications, and aims to provide you with an understanding of the underlying principles, techniques, and practical use cases of Generative AI models.

The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin.

This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art.

This book provides a practical and fairly comprehensive review of Data Science through the lens of dimensionality reduction, as well as hands-on techniques to tackle problems with data collected in the real world.

This book introduces the point cloud; its applications in industry, and the most frequently used datasets.

Machine learning methods have lowered the cost of exploring new structures of unknown compounds, and can be used to predict reasonable expectations and subsequently validated by experimental results.

This volume discusses recent advances in Artificial Intelligence (AI) applications in smart, internet-connected societies, highlighting three key focus areas.

This book explores how visualization provides an effective way of improving not only the interpretability but also the generalization capabilities of machine learning models.

This book is written both for readers entering the field, and for practitioners with a background in AI and an interest in developing real-world applications.

This book is devoted to the emerging field of integrated visual knowledge discovery that combines advances in artificial intelligence/machine learning and visualization/visual analytic.

This book is the result of a multi-year research project led and sponsored by the University of Chieti-Pescara, National Chengchi University, University of Salamanca, and Osaka University.

This book sheds light on the challenges facing social media in combating malicious accounts, and aims to introduce current practices to address the challenges.

Today, emerging technologies offer a new pathway for advancing the economy in the fields of banking, finance, and capital markets.

This SpringerBrief presents novel methods of approaching challenging problems in the reconstruction of accurate 3D models and serves as an introduction for further 3D reconstruction methods.

This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice.

This book reports on research and developments in human-technology interaction.

This book provides insights into smart ways of computer log data analysis, with the goal of spotting adversarial actions.

This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2020 in October 2020.

This proceedings book includes the results from the International Conference on Deep Learning, Artificial Intelligence and Robotics, held in Malaviya National Institute of Technology, Jawahar Lal Nehru Marg, Malaviya Nagar, Jaipur, Rajasthan, 302017.

This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT).

This book provides an overview of different deep learning-based methods for face recognition and related problems.

This book constitutes the refereed proceedings of the 10th International Workshop on Clinical Image-Based Procedures, CLIP 2021, Second MICCAI Workshop on Distributed and Collaborative Learning, DCL 2021, First MICCAI Workshop, LL-COVID19, First Secure and Privacy-Preserving Machine Learning for Medical Imaging Workshop and Tutorial, PPML 2021, held in conjunction with MICCAI 2021, in October 2021.

This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing.