4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CV2022
End-to-end Multiple Instance Learning with Gradient Accumulation
Axel Andersson, Nadezhda Koriakina, Nataša Sladoje +1
Being able to learn on weakly labeled data, and provide interpretability, are two of the main reasons why attention-based deep multiple instance learning (ABMIL) methods have becom…
eess.IV2022★ 4 cited
Oral cancer detection and interpretation: Deep multiple instance learning versus conventional deep single instance learning
Nadezhda Koriakina, Nataša Sladoje, Vladimir Bašić +1
The current medical standard for setting an oral cancer (OC) diagnosis is histological examination of a tissue sample from the oral cavity. This process is time consuming and more…