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Document type:
Konferenzbeitrag 
Contribution type:
Textbeitrag / Aufsatz 
Author(s):
Brunner, Thomas; Diehl, Frederik; Truong Le, Michael; Knoll, Alois 
Title:
Leveraging Semantic Embeddings for Safety-Critical Applications 
Pages contribution:
1389-1394 
Abstract:
Semantic Embeddings are a popular way to represent knowledge in the field of zero-shot learning. We observe their interpretability and discuss their potential utility in a safety-critical context. Concretely, we propose to use them to add introspection and error detection capabilities to neural network classifiers. First, we show how to create embeddings from symbolic domain knowledge. We discuss how to use them for interpreting mispredictions and propose a simple error detection scheme. We then...    »
 
Book / Congress title:
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 
Congress (additional information):
Long Beach, CA, USA 
Publisher:
IEEE 
Year:
2019 
Month:
Jun 
E-ISBN:
978-1-7281-2506-0 
Reviewed:
ja 
Fulltext / DOI:
Notes:
Oral (spotlight) presentation at the Workshop for Safe Artificial Intelligence for Automated Driving.