A study on relationship between prediction uncertainty and robustness to noisy data-Reference-Cited by-同舟云学术

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A study on relationship between prediction uncertainty and robustness to noisy data

Published:2023-01-31 Issue:6 Volume:54 Page:1243-1258
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

Khan Hufsa¹^ORCID,Wang Xizhao¹²^ORCID,Liu Han¹²^ORCID

Affiliation:

1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, People's Republic of China

2. Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, Guangdong, People's Republic of China

Funder

National Natural Science Foundation of China, Guangdong province

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207721.2023.2169059

Reference47 articles.

1. Systematic review of artificial intelligence techniques in the detection and classification of COVID-19 medical images in terms of evaluation and benchmarking: Taxonomy analysis, challenges, future solutions and methodological aspects

2. Image classification with deep learning in the presence of noisy labels: A survey

3. Improving test case selection by handling class and attribute noise

4. Fuzzy C-Means clustering algorithm for data with unequal cluster sizes and contaminated with noise and outliers: Review and development

5. Consumer-Driven Demand-Side Management Using K-Mean Clustering and Integer Programming in Standalone Renewable Grid

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