東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Intelligent and fuzzy systems = artificial intelligence in human-centric, resilient and sustainable industries, proceedings of the INFUS 2025 Conference.. Volume 2 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Intelligent and fuzzy systems/ edited by Cengiz Kahraman ... [et al.].
其他題名:	artificial intelligence in human-centric, resilient and sustainable industries, proceedings of the INFUS 2025 Conference.
其他題名:	INFUS 2025 Conference
其他作者:	Kahraman, Cengiz.
團體作者:	International Conference on Intelligent and Fuzzy Systems
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xv, 820 p. :ill. (some col.), digital ;24 cm.
內容註:	Deep Learning Assisted Optimization for End-effector Position and Orientation -- Multi Modal Deep Learning for Earthquake Damage Detection Integrating SAR and Optical Imagery -- AirQ ResUNet A Residual U Net Based Deep Learning Surrogate for High Resolution PM2.5 Prediction in Urban Environments -- Deep Learning Based Earthquake Prediction Magnitude and Depth Estimation Using ConvLSTM -- A Deep Learning Approach to Sentiment Classification Insights from Product Review Analysis.
Contained By:	Springer Nature eBook
標題:	Data mining - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-97992-7
ISBN:	9783031979927

Intelligent and fuzzy systems = artificial intelligence in human-centric, resilient and sustainable industries, proceedings of the INFUS 2025 Conference.. Volume 2 /
Intelligent and fuzzy systemsartificial intelligence in human-centric, resilient and sustainable industries, proceedings of the INFUS 2025 Conference.Volume 2 /[electronic resource] :INFUS 2025 Conferenceedited by Cengiz Kahraman ... [et al.]. - Cham :Springer Nature Switzerland :2025. - xv, 820 p. :ill. (some col.), digital ;24 cm. - Lecture notes in networks and systems,15292367-3389 ;. - Lecture notes in networks and systems ;1529..

Deep Learning Assisted Optimization for End-effector Position and Orientation -- Multi Modal Deep Learning for Earthquake Damage Detection Integrating SAR and Optical Imagery -- AirQ ResUNet A Residual U Net Based Deep Learning Surrogate for High Resolution PM2.5 Prediction in Urban Environments -- Deep Learning Based Earthquake Prediction Magnitude and Depth Estimation Using ConvLSTM -- A Deep Learning Approach to Sentiment Classification Insights from Product Review Analysis.

Artificial Intelligence in Human-Centric, Resilient & Sustainable Industries This book focuses on benefiting artificial intelligent tools in our business and social life under emerging conditions. Human-centric, resilient, and sustainable industries are built on ideals like human-centricity, ecological advantages, or social benefits. The mission of human-centric artificial intelligence is to improve people's lives by offering solutions that boost productivity, accessibility to resources, security, well-being, and general quality of life. The latest intelligent methods and techniques on human-centric, resilient, and sustainable industries are introduced by theory and applications. This book covers the chapters of world-wide known experts on machine learning, medical image processing, process intelligence, process mining, and others. The intended readers are intelligent systems researchers, lecturers, M.Sc. and Ph.D. students trying to develop approaches giving human needs, values, and viewpoints top priority through artificial intelligent systems.

ISBN: 9783031979927

Standard No.: 10.1007/978-3-031-97992-7doiSubjects--Topical Terms:

551626
Data mining
--Congresses.

LC Class. No.: QA76.9.D343 / I58 2025

Dewey Class. No.: 006.312

Intelligent and fuzzy systems = artificial intelligence in human-centric, resilient and sustainable industries, proceedings of the INFUS 2025 Conference.. Volume 2 /
LDR:02798nmm a2200349 a 4500 001 2413962
003 DE-He213
005 20250726130234.0
006 m d
007 cr nn 008maaau
008 260205s2025 sz s 0 eng d
020 $a 9783031979927 $q (electronic bk.)
020 $a 9783031979910 $q (paper)
024 7 $a 10.1007/978-3-031-97992-7 $2 doi
035 $a 978-3-031-97992-7
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343 $b I58 2025
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b I61 2025
111 2 $a International Conference on Intelligent and Fuzzy Systems $n (7th : $d 2025 : $c Istanbul, Turkey) $3 3790374
245 1 0 $a Intelligent and fuzzy systems $h [electronic resource] : $b artificial intelligence in human-centric, resilient and sustainable industries, proceedings of the INFUS 2025 Conference. $n Volume 2 / $c edited by Cengiz Kahraman ... [et al.].
246 3 $a INFUS 2025 Conference
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xv, 820 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in networks and systems, $x 2367-3389 ; $v 1529
505 0 $a Deep Learning Assisted Optimization for End-effector Position and Orientation -- Multi Modal Deep Learning for Earthquake Damage Detection Integrating SAR and Optical Imagery -- AirQ ResUNet A Residual U Net Based Deep Learning Surrogate for High Resolution PM2.5 Prediction in Urban Environments -- Deep Learning Based Earthquake Prediction Magnitude and Depth Estimation Using ConvLSTM -- A Deep Learning Approach to Sentiment Classification Insights from Product Review Analysis.
520 $a Artificial Intelligence in Human-Centric, Resilient & Sustainable Industries This book focuses on benefiting artificial intelligent tools in our business and social life under emerging conditions. Human-centric, resilient, and sustainable industries are built on ideals like human-centricity, ecological advantages, or social benefits. The mission of human-centric artificial intelligence is to improve people's lives by offering solutions that boost productivity, accessibility to resources, security, well-being, and general quality of life. The latest intelligent methods and techniques on human-centric, resilient, and sustainable industries are introduced by theory and applications. This book covers the chapters of world-wide known experts on machine learning, medical image processing, process intelligence, process mining, and others. The intended readers are intelligent systems researchers, lecturers, M.Sc. and Ph.D. students trying to develop approaches giving human needs, values, and viewpoints top priority through artificial intelligent systems.
650 0 $a Data mining $v Congresses. $3 551626
650 0 $a Machine learning $x Congresses. $3 576368
650 0 $a Big data $v Congresses. $3 3166510
650 0 $a Fuzzy sets $v Congresses. $3 606820
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Data Engineering. $3 3409361
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Kahraman, Cengiz. $3 923891
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in networks and systems ; $v 1529. $3 3790375
856 4 0 $u https://doi.org/10.1007/978-3-031-97992-7
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)