Data labeling: An empirical investigation into industrial challenges and mitigation strategies T Fredriksson, DI Mattos, J Bosch, HH Olsson International Conference on Product-Focused Software Process Improvement …, 2020 | 103 | 2020 |
Machine Learning Models for Automatic Labeling: A Systematic Literature Review. T Fredriksson, J Bosch, HH Olsson ICSOFT, 552-561, 2020 | 13 | 2020 |
An Empirical Evaluation of Algorithms for Data Labeling T Fredriksson, DI Mattos, J Bosch, HH Olsson 2021 IEEE 45th Annual Computers, Software, and Applications Conference …, 2021 | 5 | 2021 |
Assessing the suitability of semi-supervised learning datasets using item response theory T Fredriksson, DI Mattos, J Bosch, HH Olsson 2021 47th Euromicro Conference on Software Engineering and Advanced …, 2021 | 4 | 2021 |
Machine learning algorithms for labeling: Where and how they are used? T Fredriksson, J Bosch, HH Olsson, DI Mattos 2022 IEEE International Systems Conference (SysCon), 1-8, 2022 | 3 | 2022 |
Classification of Complex-Valued Radar Data using Semi-Supervised Learning: a Case Study T Fredriksson, J Bosch, HH Olsson 2023 49th Euromicro Conference on Software Engineering and Advanced …, 2023 | | 2023 |
Opportunities, Challenges and Solutions for Automatic Labeling of Data Using Machine Learning T Fredriksson PQDT-Global, 2023 | | 2023 |
2023 49th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)| 979-8-3503-4235-2/23/$31.00© 2023 IEEE| DOI: 10.1109/SEAA60479. 2023.00072 M Abdullah, S Abdul-Rahman, M Adil, MO Ahmad, X Alberdi, NB Ali, ... | | |
2021 47th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)| 978-1-6654-2705-0/21/$31.00© 2021 IEEE| DOI: 10.1109/SEAA53835. 2021.00058 C Almeida, S Alonso, C Alves, H Aman, S Amasaki, G Andrade, L Angelis, ... | | |
Machine Learning Algorithms for Data Labeling: An Empirical Evaluation TA Fredriksson, DI Mattos, J Bosch, HH Olsson | | |