Explainable Artificial Intelligence to Enhance Data Trustworthiness in Crowd-Sensing Systems-Reference-Cited by-同舟云学术

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Explainable Artificial Intelligence to Enhance Data Trustworthiness in Crowd-Sensing Systems

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT)
language:
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Author:

Afzal-Houshmand Sam¹,Papamartzivanos Dimitrios²,Homayoun Sajad¹,Veliou Entso³,Jensen Christian D.¹,Voulodimos Athanasios⁴,Giannetsos Thanassis²

Affiliation:

1. Technical University of Denmark (DTU),Cyber Security Section,Denmark

2. Ubitech Ltd., Digital Security & Trusted Computing Group,Greece

3. University of West Attica,Department of Informatics and Computer Engineering,Athens,Greece

4. School of Electrical & Computer Engineering, National Technical Univ. of Athens,Greece

Funder

European Commission

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10256660/10257181/10257256.pdf?arnumber=10257256

Reference28 articles.

1. Interpreting financial time series with shap values;mokhtari;Proceedings of the 29th Annual International Conference on Computer Science and Software Engineering ser CASCON '19,2019

2. Electric Energy Consumption Prediction by Deep Learning with State Explainable Autoencoder

3. Explainable AI: A Review of Machine Learning Interpretability Methods

4. Deco: False data detection and correction framework for participatory sensing

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