120 citations · 135 across the 2 of their papers we have counts for
8 papers
Classifying bacteria clones using attention-based deep multiple instance learning interpreted by persistence homology
Adriana Borowa, Dawid Rymarczyk, Dorota Ochońska +2
In this work, we analyze if it is possible to distinguish between different clones of the same bacteria species (Klebsiella pneumoniae) based only on microscopic images. It is a ch…
Deep learning approach to describe and classify fungi microscopic images
Bartosz Zieliński, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk +2
Preliminary diagnosis of fungal infections can rely on microscopic examination. However, in many cases, it does not allow unambiguous identification of the species by microbiologis…
Deep learning approach to description and classification of fungi microscopic images
Bartosz Zieliński, Agnieszka Sroka-Oleksiak, Dawid Rymarczyk +2
Diagnosis of fungal infections can rely on microscopic examination, however, in many cases, it does not allow unambiguous identification of the species due to their visual similari…
Persistence Bag-of-Words for Topological Data Analysis
Bartosz Zieliński, Michał Lipiński, Mateusz Juda +2
Persistent homology (PH) is a rigorous mathematical theory that provides a robust descriptor of data in the form of persistence diagrams (PDs). PDs exhibit, however, complex struct…
Processing of missing data by neural networks
Marek Smieja, Łukasz Struski, Jacek Tabor +2
We propose a general, theoretically justified mechanism for processing missing data by neural networks. Our idea is to replace typical neuron's response in the first hidden layer b…
Cascade context encoder for improved inpainting
Bartosz Zieliński, Łukasz Struski, Marek Śmieja +1
In this paper, we analyze if cascade usage of the context encoder with increasing input can improve the results of the inpainting. For this purpose, we train context encoder for 64…