EvalDNN: A Toolbox for Evaluating Deep Neural Network Models

Recent studies have shown that the performance of deep learning models should be evaluated using various important metrics such as robustness and neuron coverage, besides the widely-used prediction accuracy metric. However, major deep learning frameworks currently only provide APIs to evaluate a mod...

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Bibliographic Details

Published in:	Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings pp. 45 - 48
Main Authors:	Tian, Yongqiang, Zeng, Zhihua, Wen, Ming, Liu, Yepang, Kuo, Tzu-yang, Cheung, Shing-Chi
Format:	Conference Proceeding
Language:	English
Published:	ACM 01.10.2020
Subjects:	Benchmark testing Deep learning Deep Learning Model Evaluation Load modeling Measurement Neurons Robustness
Online Access:	Get full text
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