Explainable and Interpretable Models in Computer Vision and Machine Learning (Registro nro. 242306)

MARC details
000 -LIDER
fixed length control field 05528nam a22006255i 4500
001 - CONTROL NUMBER
control field 978-3-319-98131-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20210201191333.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 181129s2018 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783319981314
-- 978-3-319-98131-4
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
245 10 - TITLE STATEMENT
Title Explainable and Interpretable Models in Computer Vision and Machine Learning
Medium [electronic resource] /
Statement of responsibility, etc. edited by Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baró, Yağmur Güçlütürk, Umut Güçlü, Marcel van Gerven.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2018.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2018.
300 ## - PHYSICAL DESCRIPTION
Extent XVII, 299 p. 73 illus., 58 illus. in color.
Other physical details online resource.
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-- computer
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-- online resource
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347 ## -
-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement The Springer Series on Challenges in Machine Learning,
International Standard Serial Number 2520-131X
500 ## - GENERAL NOTE
General note Acceso multiusuario
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 1 Considerations for Evaluation and Generalization in Interpretable Machine Learning -- 2 Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges -- 3 Learning Functional Causal Models with Generative Neural Networks -- 4 Learning Interpretable Rules for Multi-label Classification -- 5 Structuring Neural Networks for More Explainable Predictions -- 6 Generating Post-Hoc Rationales of Deep Visual Classification Decisions -- 7 Ensembling Visual Explanations -- 8 Explainable Deep Driving by Visualizing Causal Action -- 9 Psychology Meets Machine Learning: Interdisciplinary Perspectives on Algorithmic Job Candidate Screening -- 10 Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions -- 11 On the Inherent Explainability of Pattern Theory-based Video Event Interpretations. .
520 ## - SUMMARY, ETC.
Summary, etc. This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning. Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning · Explanation Methods in Deep Learning · Learning Functional Causal Models with Generative Neural Networks · Learning Interpreatable Rules for Multi-Label Classification · Structuring Neural Networks for More Explainable Predictions · Generating Post Hoc Rationales of Deep Visual Classification Decisions · Ensembling Visual Explanations · Explainable Deep Driving by Visualizing Causal Attention · Interdisciplinary Perspective on Algorithmic Job Candidate Search · Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations.
541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE
Owner UABC ;
Method of acquisition Temporal ;
Date of acquisition 01/01/2021-12/31/2023.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Optical data processing.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Pattern recognition.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Artificial Intelligence.
-- https://scigraph.springernature.com/ontologies/product-market-codes/I21000
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Image Processing and Computer Vision.
-- https://scigraph.springernature.com/ontologies/product-market-codes/I22021
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Pattern Recognition.
-- https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Escalante, Hugo Jair.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Escalera, Sergio.
Relator term editor.
-- (orcid)0000-0003-0617-8873
-- https://orcid.org/0000-0003-0617-8873
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Guyon, Isabelle.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Baró, Xavier.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Güçlütürk, Yağmur.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Güçlü, Umut.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name van Gerven, Marcel.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783319981307
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9783319981321
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title The Springer Series on Challenges in Machine Learning,
-- 2520-131X
856 40 - ELECTRONIC LOCATION AND ACCESS
Public note Libro electrónico
Uniform Resource Identifier http://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-98131-4
912 ## -
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Libro Electrónico
Existencias
Estado de retiro Colección Ubicación permanente Ubicación actual Fecha de ingreso Total Checkouts Date last seen Número de copia Tipo de material
  Colección de Libros Electrónicos Biblioteca Electrónica Biblioteca Electrónica 01/02/2021   01/02/2021 1 Libro Electrónico

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