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Umeå universitet
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Huvudmenyn dold.

Saeideh Ghanbari Azar

Kontakt

E-post
saeideh.azar@umu.se

Verksam som

Anknytning
Postdoktor vid Institutionen för diagnostik och intervention
Plats
5A, Målpunkt H62, Norrlands universitetssjukhus Umeå universitet, 901 85 Umeå SE
Generalization, imbalance, and data generation in machine learning
Report / UMINF, 26.11
Ghanbari Azar, Saeideh
Rethinking the deepsmote penalty term and its role in imbalanced learning
2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI): Proceedings, IEEE 2025 : 1110-1116
Ghanbari Azar, Saeideh; Nyholm, Tufve; Löfstedt, Tommy
From promise to practice: a study of common pitfalls behind the generalization gap in machine learning
Transactions on Machine Learning Research
Ghanbari Azar, Saeideh; Tronchin, Lorenzo; Simkó, Attila; et al.
Representation-conditioned diffusion models for imbalanced image recognition
Ghanbari Azar, Saeideh; Karthikeyan, Nithesh Chandher; Nyholm, Tufve; et al.
Latent space oversampling for adult–pediatric imbalance in brain tumor segmentation
Ghanbari Azar, Saeideh; Nyholm, Tufve; Löfstedt, Tommy
Visa publikationer i DiVA