Téléchargez le livre : Explainable and Interpretable Models in Computer Vision and Machine Learning

Explainable and Interpretable Models in Computer Vision and Machine Learning



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Éditeur :

Springer


Collection :

The Springer Series on Challenges in Machine Learning

Paru le : 2018-11-29



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Description


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
Pages
299 pages
Collection
The Springer Series on Challenges in Machine Learning
Parution
2018-11-29
Marque
Springer
EAN papier
9783319981307
EAN PDF
9783319981314
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
29
Taille du fichier
9267 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
147,69 €
EAN EPUB
9783319981314
Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
29
Taille du fichier
38840 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
147,69 €

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