Data annotation quality in smart farming industry-Reference-Cited by-同舟云学术

Data annotation quality in smart farming industry

Published:2024-07-10 Issue:1 Volume:12 Page:
ISSN:2169-3277
Container-title:Production & Manufacturing Research
language:en
Short-container-title:Production & Manufacturing Research

Author:

Silva Catarina¹,Costa Dinis¹,Costa Joana¹²,Ribeiro Bernardete¹

Affiliation:

1. Department of Informatics Engineering, CISUC/LASI - Center for Informatics and Systems of the University of Coimbra, Coimbra, Portugal

2. Department of Informatics Engineering, School of Technology and Management, Polytechnic of Leiria, Leiria, Portugal

Funder

Fundação para a Ciência e a Tecnologia

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/21693277.2024.2377253

Reference23 articles.

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3. Chen, Y., Santosa, A. E., Yi, A. M., Sharma, A., Sharma, A., & Lo, D. A. (2020). A machine learning approach for vulnerability curation. 2020 IEEE/ACM 17th International Conference on Mining Software Repositories (MSR) (pp. 32–42.

4. Costa, D., Silva, C., Costa, J., & Ribeiro, B. (2023). Enhancing pest detection models through improved anno- tations. In N. Moniz, Z. Vale, & J. Cascalho (Eds.), Progress in artificial intelligence (pp. 364–375). Springer Nature Switzerland.

5. Active learning by learning;Hsu W. N.;Proceedings of the AAAI Conference on Artificial Intelligence,2015