Evaluating Deep Neural Networks in Deployment: A Comparative Study (Replicability Study)-Reference-Cited by-同舟云学术

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Evaluating Deep Neural Networks in Deployment: A Comparative Study (Replicability Study)

Published:2024-09-11 Issue: Volume:2 Page:1300-1311
ISSN:
Container-title:Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis
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Author:

Pinconschi Eduard¹^ORCID,Gopinath Divya²^ORCID,Abreu Rui³^ORCID,Păsăreanu Corina S.⁴^ORCID

Affiliation:

1. Carnegie Mellon University, Pittsburgh, USA

2. KBR Inc., Mountain View, USA / NASA Ames, Mountain View, USA

3. INESC-ID, Porto, Portugal / University of Porto, Porto, Portugal

4. Carnegie Mellon University, Mountain View, USA / NASA Ames, Mountain View, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3650212.3680401

Reference33 articles.

1. [n. d.]. Keras documentation: CIFAR10 small images classification dataset. https://keras.io/api/datasets/cifar10/ Accessed on 2024-09-11

2. 2016. Pima Indians Diabetes Dataset. https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database Accessed on 2024-09-11

3. 2018. Bank Marketing Dataset. https://www.kaggle.com/datasets/sharanmk/bank-marketing-term-deposit Accessed on 2024-09-11

4. 2019. German Credit Risk Classification with Keras. https://www.kaggle.com/code/twunderbar/german-credit-risk-classification-with-keras/data Accessed on 2024-09-11

5. 2019. House Price Prediction Dataset. https://www.kaggle.com/datasets/moewie94/housepricedata Accessed on 2024-09-11

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