Cognitive Fairness Aware Techniques For Human Machine Interface(1st Edition)

Authors:

Vithya Ganesan ,S Indu Vadhani ,Subrata Chowdhury ,Souvik Pal ,Vishnu S Pendyala

Type:Hardcover/ PaperBack / Loose Leaf
Condition: Used/New

In Stock: 2 Left

Shipment time

Expected shipping within 2 - 3 Days
Access to 35 Million+ Textbooks solutions Free
Ask Unlimited Questions from expert AI-Powered Answers 30 Min Free Tutoring Session
7 days-trial

Total Price:

$126

List Price: $180.00 Savings: $54 (30%)
Access to 30 Million+ solutions
Ask 50 Questions from expert AI-Powered Answers 24/7 Tutor Help Detailed solutions for Cognitive Fairness Aware Techniques For Human Machine Interface

Price:

$9.99

/month

Book details

ISBN: 103276709X, 978-1032767093

Book publisher: Chapman and Hall/CRC

Book Price $126 : 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.â?¢ 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 Communicationâ?¢ Discusses Emotional Data Processing Challenges Through AI Accelerator With Federated Learning Module To Generate Periodical Counselling Messagesâ?¢ Data Analysis Anomalies Are Addressed In Graph Data Base Modelling By Anomaly Prediction And Anomaly Detectionâ?¢ Describes 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.