Year: 2019
Type: conference-paper
Abstract: With the increasing adoption of Deep Neural Network (DNN) models as integral parts of software systems, efficient operational testing of DNNs is much in demand to ensure these models' actual performance in field conditions. A challenge is that the testing often needs to produce precise results with a very limited budget for labeling data collected in field.
Authors: Zenan Li, Xiaoxing Ma, Chang Xu, Chun Cao, Jingwei Xu, Jian Lü
Institution: Nanjing University
Language: English
Subfield: Software
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Award: G3442037871
OpenAlex ID: W2948254043