國立虎尾科技大學 |

Artificial Intelligence for Human Computer Interaction: A Modern Approach

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Artificial Intelligence for Human Computer Interaction: A Modern Approach/ edited by Yang Li, Otmar Hilliges.
other author:	Li, Yang.
Description:	XX, 595 p. 228 illus., 216 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	User interfaces (Computer systems). -
Online resource:	https://doi.org/10.1007/978-3-030-82681-9
ISBN:	9783030826819

Artificial Intelligence for Human Computer Interaction: A Modern Approach
Artificial Intelligence for Human Computer Interaction: A Modern Approach[electronic resource] /edited by Yang Li, Otmar Hilliges. - 1st ed. 2021. - XX, 595 p. 228 illus., 216 illus. in color.online resource. - Human–Computer Interaction Series,2524-4477. - Human–Computer Interaction Series,.

Introduction -- Part 1: Modeling -- Human performance modeling with deep learning -- Optimal control to support high-level user goals in human-computer interaction.-Modeling UI tappability using deep learning and crowdsourcing -- Part 2: Input -- Eye gaze estimation and its applications -- AI-driven intelligent text correction techniques for mobile text entry -- Deep touch: Sensing press gestures from touch image sequences -- Deep learning-based hand posture recognition for pen interaction enhancement -- Part 3: Data and tools -- An early Rico retrospective: Three years of uses for a mobile app dataset -- Visual intelligence through human interaction -- ML tools for the web: A way for rapid prototyping and HCI research -- Interactive reinforcement learning for autonomous behavior design -- Part 4: Specific domains -- Sketch-based creativity support tools using deep learning -- Generative link: Data-driven computational models for digital ink -- Bridging natural language and graphical user interfaces -- Demonstration + natural language: Multimodal interfaces for GUI-based interactive task learning agents -- Human-centred AI for medical imaging -- 3D spatial sound individualization with perceptual feedback.

This edited book explores the many interesting questions that lie at the intersection between AI and HCI. It covers a comprehensive set of perspectives, methods and projects that present the challenges and opportunities that modern AI methods bring to HCI researchers and practitioners. The chapters take a clear departure from traditional HCI methods and leverage data-driven and deep learning methods to tackle HCI problems that were previously challenging or impossible to address. It starts with addressing classic HCI topics, including human behaviour modeling and input, and then dedicates a section to data and tools, two technical pillars of modern AI methods. These chapters exemplify how state-of-the-art deep learning methods infuse new directions and allow researchers to tackle long standing and newly emerging HCI problems alike. Artificial Intelligence for Human Computer Interaction: A Modern Approach concludes with a section on Specific Domains which covers a set of emerging HCI areas where modern AI methods start to show real impact, such as personalized medical, design, and UI automation.

ISBN: 9783030826819

Standard No.: 10.1007/978-3-030-82681-9doiSubjects--Topical Terms:

1253526
User interfaces (Computer systems).

LC Class. No.: QA76.9.U83

Dewey Class. No.: 005.437

Artificial Intelligence for Human Computer Interaction: A Modern Approach
LDR:03835nam a22004335i 4500 001 1056949
003 DE-He213
005 20211104063123.0
007 cr nn 008mamaa
008 220103s2021 sz | s |||| 0|eng d
020 $a 9783030826819 $9 978-3-030-82681-9
024 7 $a 10.1007/978-3-030-82681-9 $2 doi
035 $a 978-3-030-82681-9
050 4 $a QA76.9.U83
050 4 $a QA76.9.H85
072 7 $a UYZG $2 bicssc
072 7 $a COM070000 $2 bisacsh
072 7 $a UYZG $2 thema
082 0 4 $a 005.437 $2 23
082 0 4 $a 4.019 $2 23
245 1 0 $a Artificial Intelligence for Human Computer Interaction: A Modern Approach $h [electronic resource] / $c edited by Yang Li, Otmar Hilliges.
250 $a 1st ed. 2021.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a XX, 595 p. 228 illus., 216 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Human–Computer Interaction Series, $x 2524-4477
505 0 $a Introduction -- Part 1: Modeling -- Human performance modeling with deep learning -- Optimal control to support high-level user goals in human-computer interaction.-Modeling UI tappability using deep learning and crowdsourcing -- Part 2: Input -- Eye gaze estimation and its applications -- AI-driven intelligent text correction techniques for mobile text entry -- Deep touch: Sensing press gestures from touch image sequences -- Deep learning-based hand posture recognition for pen interaction enhancement -- Part 3: Data and tools -- An early Rico retrospective: Three years of uses for a mobile app dataset -- Visual intelligence through human interaction -- ML tools for the web: A way for rapid prototyping and HCI research -- Interactive reinforcement learning for autonomous behavior design -- Part 4: Specific domains -- Sketch-based creativity support tools using deep learning -- Generative link: Data-driven computational models for digital ink -- Bridging natural language and graphical user interfaces -- Demonstration + natural language: Multimodal interfaces for GUI-based interactive task learning agents -- Human-centred AI for medical imaging -- 3D spatial sound individualization with perceptual feedback.
520 $a This edited book explores the many interesting questions that lie at the intersection between AI and HCI. It covers a comprehensive set of perspectives, methods and projects that present the challenges and opportunities that modern AI methods bring to HCI researchers and practitioners. The chapters take a clear departure from traditional HCI methods and leverage data-driven and deep learning methods to tackle HCI problems that were previously challenging or impossible to address. It starts with addressing classic HCI topics, including human behaviour modeling and input, and then dedicates a section to data and tools, two technical pillars of modern AI methods. These chapters exemplify how state-of-the-art deep learning methods infuse new directions and allow researchers to tackle long standing and newly emerging HCI problems alike. Artificial Intelligence for Human Computer Interaction: A Modern Approach concludes with a section on Specific Domains which covers a set of emerging HCI areas where modern AI methods start to show real impact, such as personalized medical, design, and UI automation.
650 0 $a User interfaces (Computer systems). $3 1253526
650 0 $a Artificial intelligence. $3 559380
650 1 4 $a User Interfaces and Human Computer Interaction. $3 669793
650 2 4 $a Artificial Intelligence. $3 646849
700 1 $a Li, Yang. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 866770
700 1 $a Hilliges, Otmar. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1362341
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030826802
776 0 8 $i Printed edition: $z 9783030826826
776 0 8 $i Printed edition: $z 9783030826833
830 0 $a Human–Computer Interaction Series, $x 1571-5035 $3 1254242
856 4 0 $u https://doi.org/10.1007/978-3-030-82681-9
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)