Machine learning paradigms advances (63 risultati)
Lingua: Inglese
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Lingua: Inglese
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Lingua: Inglese
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Serie: Libro 128 di 188 - Intelligent Systems Reference Library
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Machine Learning Paradigms : Advances in Learning Analytics
Virvou, Maria (EDT); Alepis, Efthimios (EDT); Tsihrintzis, George A. (EDT); Jain, Lakhmi C. (EDT)
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 128 di 188 - Intelligent Systems Reference Library
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Machine Learning Paradigms : Advances in Learning Analytics
Virvou, Maria (EDT); Alepis, Efthimios (EDT); Tsihrintzis, George A. (EDT); Jain, Lakhmi C. (EDT)
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 128 di 188 - Intelligent Systems Reference Library
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Machine Learning Paradigms : Advances in Learning Analytics
Virvou, Maria (EDT); Alepis, Efthimios (EDT); Tsihrintzis, George A. (EDT); Jain, Lakhmi C. (EDT)
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 128 di 188 - Intelligent Systems Reference Library
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Serie: Libro 18 di 29 - Learning and Analytics in Intelligent Systems
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Machine Learning Paradigms : Advances in Learning Analytics
Virvou, Maria (EDT); Alepis, Efthimios (EDT); Tsihrintzis, George A. (EDT); Jain, Lakhmi C. (EDT)
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 128 di 188 - Intelligent Systems Reference Library
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Hardcover. Condizione: new. Hardcover. This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection…frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.This book provides numerous ways that deep learners can use for logo recognition, including:Deep learning-based end-to-end trainable architecture for logo detectionWeakly supervised logo recognition approach using attention mechanismsAnchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world imagesUnsupervised logo detection that takes into account domain-shift issues from synthetic to real-world imagesApproach for logo detection modeling domain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 120 di 188 - Intelligent Systems Reference Library
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Machine Learning Paradigms : Advances in Data Analytics
Tsihrintzis, George A. (EDT); Sotiropoulos, Dionisios N. (EDT); Jain, Lakhmi C. (EDT)
Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 120 di 188 - Intelligent Systems Reference Library
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Machine Learning Paradigms : Advances in Data Analytics
Tsihrintzis, George A. (EDT); Sotiropoulos, Dionisios N. (EDT); Jain, Lakhmi C. (EDT)
Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 120 di 188 - Intelligent Systems Reference Library
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Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 128 di 188 - Intelligent Systems Reference Library
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Altre immaginiLingua: Inglese
Editore: Springer, 2021
Serie: Libro 18 di 29 - Learning and Analytics in Intelligent Systems
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Taschenbuch. Condizione: Neu. Machine Learning Paradigms | Advances in Deep Learning-based Technological Applications | George A. Tsihrintzis (u. a.) | Taschenbuch | Learning and Analytics in Intelligent Systems | xii | Englisch | 2021 | Springer | EAN 9783030497262 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tier…gartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer, 2021
Serie: Libro 18 di 29 - Learning and Analytics in Intelligent Systems
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Condizione: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
Machine Learning Paradigms : Advances in Data Analytics
Tsihrintzis, George A. (EDT); Sotiropoulos, Dionisios N. (EDT); Jain, Lakhmi C. (EDT)
Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 120 di 188 - Intelligent Systems Reference Library
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Machine Learning Paradigms : Advances in Data Analytics
Tsihrintzis, George A. (EDT); Sotiropoulos, Dionisios N. (EDT); Jain, Lakhmi C. (EDT)
Lingua: Inglese
Editore: Springer, 2018
Serie: Libro 120 di 188 - Intelligent Systems Reference Library
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Lingua: Inglese
Editore: Springer, 2018
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Taschenbuch. Condizione: Neu. Machine Learning Paradigms | Advances in Data Analytics | George A. Tsihrintzis (u. a.) | Taschenbuch | xvi | Englisch | 2018 | Springer | EAN 9783030067779 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbi…eter: preigu.
Lingua: Inglese
Editore: Birkhäuser, 2020
Serie: Libro 18 di 29 - Learning and Analytics in Intelligent Systems
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and di…verse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from authors who work in the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into six parts, namely (1) Deep Learning in Sensing, (2) Deep Learning in Social Media and IOT, (3) Deep Learning in the Medical Field, (4) Deep Learning in Systems Control, (5) Deep Learning in Feature Vector Processing, and (6) Evaluation of Algorithm Performance.This research book is directed towards professors, researchers, scientists, engineers and students in computer science-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent deep learning-based technological applications. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into their application areas of interest.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 128 di 188 - Intelligent Systems Reference Library
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators' and learners' data with… the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including:- Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation;- Using learning analytics to predict student performance;- Using learning analytics to create learning materials and educational courses; and- Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.
Lingua: Inglese
Editore: Birkhäuser, 2021
Serie: Libro 18 di 29 - Learning and Analytics in Intelligent Systems
- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many… and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from authors who work in the corresponding chapter theme and are recognized for their significant research contributions. In more detail, the chapters in the book are organized into six parts, namely (1) Deep Learning in Sensing, (2) Deep Learning in Social Media and IOT, (3) Deep Learning in the Medical Field, (4) Deep Learning in Systems Control, (5) Deep Learning in Feature Vector Processing, and (6) Evaluation of Algorithm Performance.This research book is directed towards professors, researchers, scientists, engineers and students in computer science-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent deep learning-based technological applications. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into their application areas of interest.
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering.
Lingua: Inglese
Editore: Springer International Publishing, Springer Nature Switzerland, 2024
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes re…cent advancement in object detection frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.This book provides numerous ways that deep learners can use for logo recognition, including:Deep learning-based end-to-end trainable architecture for logo detectionWeakly supervised logo recognition approach using attention mechanismsAnchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world imagesUnsupervised logo detection that takes into account domain-shift issues from synthetic to real-world imagesApproach for logo detection modeling domain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 128 di 188 - Intelligent Systems Reference Library
- Rilegato
Da: Buchpark, Trebbin, GermaniaBuchpark
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Condizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book presents recent machine learning paradigms and advances in learning analytics, an emerging research discipline concerned with the collection, advanced processing, and extraction of useful information from both educators¿ and lear…ners¿ data with the goal of improving education and learning systems. In this context, internationally respected researchers present various aspects of learning analytics and selected application areas, including:¿ Using learning analytics to measure student engagement, to quantify the learning experience and to facilitate self-regulation;¿ Using learning analytics to predict student performance;¿ Using learning analytics to create learning materials and educational courses; and¿ Using learning analytics as a tool to support learners and educators in synchronous and asynchronous eLearning. The book offers a valuable asset for professors, researchers, scientists, engineers and students of all disciplines. Extensive bibliographies at the end of each chapter guide readers to probe further into their application areas of interest.
