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New trends in disruptive technologies, tech ethics and artificial intelligence = the DiTTEt 2025 Collection /

Record Type:	Electronic resources : Monograph/item
Title/Author:	New trends in disruptive technologies, tech ethics and artificial intelligence/ edited by Daniel H. de la Iglesia, Juan F. de Paz Santana, Alfonso J. López Rivero.
Reminder of title:	the DiTTEt 2025 Collection /
remainder title:	DiTTEt 2025
other author:	Iglesia, Daniel H. de la.
corporate name:	International Conference on Disruptive Technologies, Tech Ethics, and Artificial Intelligence
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xv, 492 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Benchmarking DINOv2 on Large-Scale Multiclass Classification Tasks: a Flowers Case Study -- AI-Driven Personalization in Mobile Health Applications: An Elderly-Focused Approach to Health Monitoring and Prediction -- Assisted Development of an Urban Planning Ontology via Human-AI Collaboration: A Case Study in Algodre (Zamora) -- Are the graph neural networks better than standard classifiers? - Classification of skin cell structure in optical microscope images using transfer learning and watershed segmentation, etc.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligence - Congresses. - Moral and ethical aspects -
Online resource:	https://doi.org/10.1007/978-3-031-99474-6
ISBN:	9783031994746

New trends in disruptive technologies, tech ethics and artificial intelligence = the DiTTEt 2025 Collection /
New trends in disruptive technologies, tech ethics and artificial intelligencethe DiTTEt 2025 Collection /[electronic resource] :DiTTEt 2025edited by Daniel H. de la Iglesia, Juan F. de Paz Santana, Alfonso J. López Rivero. - Cham :Springer Nature Switzerland :2025. - xv, 492 p. :ill. (some col.), digital ;24 cm. - Advances in intelligent systems and computing,14652194-5365 ;. - Advances in intelligent systems and computing ;1465..

Benchmarking DINOv2 on Large-Scale Multiclass Classification Tasks: a Flowers Case Study -- AI-Driven Personalization in Mobile Health Applications: An Elderly-Focused Approach to Health Monitoring and Prediction -- Assisted Development of an Urban Planning Ontology via Human-AI Collaboration: A Case Study in Algodre (Zamora) -- Are the graph neural networks better than standard classifiers? - Classification of skin cell structure in optical microscope images using transfer learning and watershed segmentation, etc.

This book explores the latest advances in artificial intelligence, big data, the Internet of Things, and other disruptive technologies, while also addressing the ethical and social challenges they pose. It brings together peer-reviewed research presented at an international conference, offering a multidisciplinary perspective that combines technical innovation with critical reflection. The volume highlights new developments in AI applications, intelligent systems, and data-driven solutions, alongside analyses of their real-world impact. It is designed for researchers, postgraduate students, developers, and decision-makers interested in both cutting-edge technological progress and its broader implications. By connecting technical achievements with ethical and societal considerations, the book provides a comprehensive view of how innovation can be guided responsibly in diverse fields such as healthcare, climate science, politics, and cybersecurity.

ISBN: 9783031994746

Standard No.: 10.1007/978-3-031-99474-6doiSubjects--Topical Terms:

3384368
Artificial intelligence
--Moral and ethical aspects--Congresses.

LC Class. No.: Q334.7

Dewey Class. No.: 174.90063

New trends in disruptive technologies, tech ethics and artificial intelligence = the DiTTEt 2025 Collection /
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520 $a This book explores the latest advances in artificial intelligence, big data, the Internet of Things, and other disruptive technologies, while also addressing the ethical and social challenges they pose. It brings together peer-reviewed research presented at an international conference, offering a multidisciplinary perspective that combines technical innovation with critical reflection. The volume highlights new developments in AI applications, intelligent systems, and data-driven solutions, alongside analyses of their real-world impact. It is designed for researchers, postgraduate students, developers, and decision-makers interested in both cutting-edge technological progress and its broader implications. By connecting technical achievements with ethical and societal considerations, the book provides a comprehensive view of how innovation can be guided responsibly in diverse fields such as healthcare, climate science, politics, and cybersecurity.
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