Proceedings of the Future Technologies Conference (FTC) 2024, Volume 1 (eBook, PDF)

Redaktion: Arai, Kohei

• Format: PDF

Produktbeschreibung

This book covers proceedings of the Future Technologies Conference (FTC) 2024 which showcase a collection of thoroughly researched studies presented at the ninth Future Technologies Conference, held in London, the UK. This premier annual event highlights groundbreaking research in artificial intelligence, computer vision, data science, computing, ambient intelligence, and related fields.

With 476 submissions, FTC 2024 gathers visionary minds to explore innovative solutions to today's most pressing challenges. The 173 selected papers represent cutting-edge advancements that foster vital conversations and future collaborations in the realm of information technologies.

The authors extend their deepest gratitude to all contributors, reviewers, and participants for making FTC 2024 an unparalleled success. The authors hope this volume inspires and informs its readers, encouraging continued exploration and innovation in future technologies.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 640
• Erscheinungstermin: 4. November 2024
• Englisch
• ISBN-13: 9783031731105
• Artikelnr.: 72065049

Inhaltsangabe

A Conditioned Unsupervised Regression Framework Attuned to the Dynamic Nature of Data Streams.- Cloud Versus Local: Performance Evaluation of Multi-Node Hadoop Clusters Using HiBench Benchmarks.- The Serial Data Processing Unit: High Performance with Parallelism in Network Processing.- Leveraging Artificial Intelligence Models Using Synthetic Data.- Tausi: A Holistic Artificial Intelligence Approach to Credit Scoring Using Informal Data for a Sustainable Micro-Lending African Economy.- Quickest Detection of Failures in Autoregressive Stochastic Systems in Short Periods.- Towards the Design of Explanation-aware Decision Support Systems.- AI to Detect Firms' Competitive Performance: An Application of Auto Contractive Map to the Hospitality Industry.- Sustainable Practices in AI and Big Data.- A Multi-Layered Approach to Evaluating Speech Translation Performance of Meetings.