Deep Learning And Applications – alle Bücher und LPs, Seite 2

Roland Schwaiger, Joachim Steinwendner
Neuronale Netze programmieren mit Python

Neuronale Netze stehen im Mittelpunkt, wenn es um Künstliche Intelligenz und Machine Learning geht. Sie revolutionieren Bild- und Spracherkennung, Spiele-KIs und vieles mehr. Zum Glück lassen sich die gen…

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Buch

Hoi-Jun Yoo, Juhyoung Lee
Deep Reinforcement Learning Processor Design for Mobile Applications

This book discusses the acceleration of deep reinforcement learning (DRL), which may be the next step in the burst success of artificial intelligence (AI). The authors address acceleration systems which e…

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Optimization, Learning Algorithms and Applications

This two-volume set, CCIS 2280 and CCIS 2281, constitutes the proceedings of the 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024, held in Tenerife, Spain, in …

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Optimization, Learning Algorithms and Applications

This two-volume set, CCIS 2280 and CCIS 2281, constitutes the proceedings of the 4th International Conference on Optimization, Learning Algorithms and Applications, OL2A 2024, held in Tenerife, Spain, in …

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Lasha Abzianidze, Lisa Bylinina, Denis Paperno
Semantics and Deep Learning

This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compos…

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Lasha Abzianidze, Lisa Bylinina, Denis Paperno
Semantics and Deep Learning

This Element covers the interaction of two research areas: linguistic semantics and deep learning. It focuses on three phenomena central to natural language interpretation: reasoning and inference; compos…

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Deep Ray, Assad A. Oberai, Orazio Pinti
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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Zekâi ¿En
Shallow and Deep Learning Principles

This book discusses Artificial Neural Networks (ANN) and their ability to predict outcomes using deep and shallow learning principles. The author first describes ANN implementation, consisting of at least…

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Charu C. Aggarwal
Neural Networks and Deep Learning

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly import…

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Practical Machine Learning Tools and Techniques for Industrial Applications

The main goal of the book is to provide a comprehensive and accessible guide that empowers readers to understand, apply, and leverage machine learning algorithms and techniques effectively in real-world s…

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Analytics Modeling in Reliability and Machine Learning and Its Applications

This book presents novel research and application chapters on topics in reliability, statistics, and machine learning. It has an emphasis on analytical models and techniques and practical applications in…

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Advancements in Machine Learning and Natural Language Processing: Innovations and Applications

This book discovers groundbreaking advancements in artificial intelligence with innovative solutions for real-world challenges. This book showcases state-of-the-art methodologies like deep learning and tr…

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Machine Learning and Other Soft Computing Techniques: Biomedical and Related Applications

This book contains applications to various health-related problems, from designing and maintaining a proper diet to enhancing hygiene to analysis of mammograms and left-right brain activity to treating di…

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Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications

This volume presents a selection of articles on statistical modeling and simulation, with a focus on different aspects of statistical estimation and testing problems, the design of experiments, reliabilit…

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

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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Johannes Jahn
Order Analysis, Deep Learning, and Connections to Optimization

This book introduces readers to order analysis and various aspects of deep learning, and describes important connections to optimization, such as nonlinear optimization as well as vector and set optimizat…

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Ali Kaveh
Applications of Artificial Neural Networks and Machine Learning in Civil Engineering

This book provides different applications of artificial neural networks (ANN) and machine learning (ML) in various problems of material science, structural optimization, and optimal analysis of structures…

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Rabia Riad, Frederic Ros
Feature and Dimensionality Reduction for Clustering with Deep Learning

This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to …

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Recent Advances in Machine Learning Techniques and Sensor Applications for Human Emotion, Activity Recognition and Support

This book explores integrating machine learning techniques and sensor applications for human emotion and activity recognition, creating personalized and effective support systems. It covers state-of-the-a…

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Abdussalam Elhanashi, Sergio Saponara
Deep Learning in Action: Image and Video Processing for Practical Use

Artificial intelligence technology has entered an extraordinary phase of fast development and wide application. The techniques developed in traditional AI research areas, such as computer vision and objec…

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