Ganesan Vithya (20 results)

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by CRC Press, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

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    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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  • Language: English

    Published by Taylor & Francis Ltd, 2025

    103276709X / 9781032767093

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    Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE

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  • Language: English

    Published by Taylor and Francis Ltd, GB, 2025

    103276709X / 9781032767093

    • Hardcover

    Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA

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    Hardback. Condition: New. This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly. The book also sheds light on emotional data processing in AI accelerators and federated learning modules. Additionally, it covers machine learning, knowledge representation, and the application of knowledge graphs to understand and optimize the behaviour of AI assistance devices.Features:Explains complex issues of Cognitive Fairness Aware Contextual Proactive Federated Protocol collects data and identifies individual emotional issues and resolves them by contextual solitary proactive communicationDiscusses emotional data processing challenges through AI accelerator with federated learning module to generate periodical counselling messagesAddresses data analysis anomalies in Graph Database Modelling by anom-aly prediction and anomaly detectionDescribes anomaly detection techniques in the form of abnormal data records, messages, events, groups, and/or other unexpected observations in graph database modellingExplains how outlier detection for data analysis deals with the detection of patterns in Graph DatabaseThis book is for researchers, academics, students, AI practitioners and developers, ethics experts in AI technology and machine-learning practitioners interested in fairness in human-machine interfaces.

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    Hardcover. Condition: Brand New. 376 pages. 9.18x6.12x9.45 inches. In Stock.

  • Language: English

    Published by Taylor and Francis Ltd, GB, 2025

    103276709X / 9781032767093

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    Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK

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    Hardback. Condition: New. This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly. The book also sheds light on emotional data processing in AI accelerators and federated learning modules. Additionally, it covers machine learning, knowledge representation, and the application of knowledge graphs to understand and optimize the behaviour of AI assistance devices.Features:Explains complex issues of Cognitive Fairness Aware Contextual Proactive Federated Protocol collects data and identifies individual emotional issues and resolves them by contextual solitary proactive communicationDiscusses emotional data processing challenges through AI accelerator with federated learning module to generate periodical counselling messagesAddresses data analysis anomalies in Graph Database Modelling by anom-aly prediction and anomaly detectionDescribes anomaly detection techniques in the form of abnormal data records, messages, events, groups, and/or other unexpected observations in graph database modellingExplains how outlier detection for data analysis deals with the detection of patterns in Graph DatabaseThis book is for researchers, academics, students, AI practitioners and developers, ethics experts in AI technology and machine-learning practitioners interested in fairness in human-machine interfaces.

  • Language: English

    Published by Taylor & Francis Ltd, 2025

    103276709X / 9781032767093

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    Hardcover. Condition: new. Hardcover. This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly. The book also sheds light on emotional data processing in AI accelerators and federated learning modules. Additionally, it covers machine learning, knowledge representation, and the application of knowledge graphs to understand and optimize the behaviour of AI assistance devices.Features:Explains complex issues of Cognitive Fairness Aware Contextual Proactive Federated Protocol collects data and identifies individual emotional issues and resolves them by contextual solitary proactive communicationDiscusses emotional data processing challenges through AI accelerator with federated learning module to generate periodical counselling messagesAddresses data analysis anomalies in Graph Database Modelling by anom-aly prediction and anomaly detectionDescribes anomaly detection techniques in the form of abnormal data records, messages, events, groups, and/or other unexpected observations in graph database modellingExplains how outlier detection for data analysis deals with the detection of patterns in Graph DatabaseThis book is for researchers, academics, students, AI practitioners and developers, ethics experts in AI technology and machine-learning practitioners interested in fairness in human-machine interfaces. This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly.The book also sheds light on emotional data processing in AI accelerators and federated learning modules. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

  • Language: English

    Published by Taylor & Francis Ltd, 2025

    103276709X / 9781032767093

    • Hardcover
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    Seller: CitiRetail, Stevenage, United KingdomCitiRetail

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    Hardcover. Condition: new. Hardcover. This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly. The book also sheds light on emotional data processing in AI accelerators and federated learning modules. Additionally, it covers machine learning, knowledge representation, and the application of knowledge graphs to understand and optimize the behaviour of AI assistance devices.Features:Explains complex issues of Cognitive Fairness Aware Contextual Proactive Federated Protocol collects data and identifies individual emotional issues and resolves them by contextual solitary proactive communicationDiscusses emotional data processing challenges through AI accelerator with federated learning module to generate periodical counselling messagesAddresses data analysis anomalies in Graph Database Modelling by anom-aly prediction and anomaly detectionDescribes anomaly detection techniques in the form of abnormal data records, messages, events, groups, and/or other unexpected observations in graph database modellingExplains how outlier detection for data analysis deals with the detection of patterns in Graph DatabaseThis book is for researchers, academics, students, AI practitioners and developers, ethics experts in AI technology and machine-learning practitioners interested in fairness in human-machine interfaces. This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly.The book also sheds light on emotional data processing in AI accelerators and federated learning modules. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

  • Language: English

    Published by Taylor & Francis Ltd, 2025

    103276709X / 9781032767093

    • Hardcover
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    Hardcover. Condition: new. Hardcover. This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly. The book also sheds light on emotional data processing in AI accelerators and federated learning modules. Additionally, it covers machine learning, knowledge representation, and the application of knowledge graphs to understand and optimize the behaviour of AI assistance devices.Features:Explains complex issues of Cognitive Fairness Aware Contextual Proactive Federated Protocol collects data and identifies individual emotional issues and resolves them by contextual solitary proactive communicationDiscusses emotional data processing challenges through AI accelerator with federated learning module to generate periodical counselling messagesAddresses data analysis anomalies in Graph Database Modelling by anom-aly prediction and anomaly detectionDescribes anomaly detection techniques in the form of abnormal data records, messages, events, groups, and/or other unexpected observations in graph database modellingExplains how outlier detection for data analysis deals with the detection of patterns in Graph DatabaseThis book is for researchers, academics, students, AI practitioners and developers, ethics experts in AI technology and machine-learning practitioners interested in fairness in human-machine interfaces. This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly.The book also sheds light on emotional data processing in AI accelerators and federated learning modules. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

  • Language: English

    Published by CRC Press, 2025

    103276709X / 9781032767093

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    Seller: moluna, Greven, Germanymoluna

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Vithya Ganesan, PhD is a professor in the Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India. Currently Principal Investigator to develop a device for visually challenged peop.

  • Language: English

    Published by Chapman and Hall/CRC, 2025

    103276709X / 9781032767093

    • Hardcover
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    Seller: preigu, Osnabrück, Germanypreigu

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    Buch. Condition: Neu. Cognitive Fairness-Aware Techniques for Human-Machine Interface | Vithya Ganesan (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2025 | Chapman and Hall/CRC | EAN 9781032767093 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

  • Language: English

    Published by Chapman And Hall/CRC, 2025

    103276709X / 9781032767093

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    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book explores the critical issue of fairness in human-machine interfaces. It delves into the integration of technology and cognitive science to develop AI systems that are unbiased, reliable, and user-friendly.The book also sheds light on emotional data processing in AI accelerators and federated learning modules.