0
Your cart

Your cart is empty

Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning

Buy Now

Explainable and Interpretable Models in Computer Vision and Machine Learning (Book, 1st ed. 2018) Loot Price: R4,171
Discovery Miles 41 710
Explainable and Interpretable Models in Computer Vision and Machine Learning (Book, 1st ed. 2018): Hugo Jair Escalante, Sergio...

Explainable and Interpretable Models in Computer Vision and Machine Learning (Book, 1st ed. 2018)

Hugo Jair Escalante, Sergio Escalera, Isabelle Guyon, Xavier Baro, Yagmur Gucluturk, Umut Guclu, Marcel van Gerven

Series: The Springer Series on Challenges in Machine Learning

 (sign in to rate)
Loot Price R4,171 Discovery Miles 41 710 | Repayment Terms: R391 pm x 12*

Bookmark and Share

Expected to ship within 10 - 15 working days

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

General

Imprint: Springer International Publishing AG
Country of origin: Switzerland
Series: The Springer Series on Challenges in Machine Learning
Release date: 2019
First published: 2018
Editors: Hugo Jair Escalante • Sergio Escalera • Isabelle Guyon • Xavier Baro • Yagmur Gucluturk • Umut Guclu • Marcel van Gerven
Dimensions: 235 x 155mm (L x W)
Format: Book • Electronic book text
Pages: 299
Edition: 1st ed. 2018
ISBN-13: 978-3-319-98130-7
Categories: Books > Computing & IT > Applications of computing > Pattern recognition
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
Books > Computing & IT > Applications of computing > Image processing > General
LSN: 3-319-98130-7
Barcode: 9783319981307

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!

Partners