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20162024
most citedDeep learning approach to description and classification of fungi microscopic images

121 citations · 416 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.CV2020★ 2 cited

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…

cs.CV2020★ 82 cited

ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery

Dawid Rymarczyk, Łukasz Struski, Jacek Tabor +1

In this paper, we introduce ProtoPShare, a self-explained method that incorporates the paradigm of prototypical parts to explain its predictions. The main novelty of the ProtoPShar…

cs.CV2020★ 120 cited

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…

cs.CV2019★ 121 cited

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…

cs.CV2018

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…

cs.CV2017★ 15 cited

A Study on Topological Descriptors for the Analysis of 3D Surface Texture

Matthias Zeppelzauer, Bartosz Zielinski, Mateusz Juda +1

Methods from computational topology are becoming more and more popular in computer vision and have shown to improve the state-of-the-art in several tasks. In this paper, we investi…

cs.CV2016★ 2 cited

Topological descriptors for 3D surface analysis

Matthias Zeppelzauer, Bartosz Zieliński, Mateusz Juda +1

We investigate topological descriptors for 3D surface analysis, i.e. the classification of surfaces according to their geometric fine structure. On a dataset of high-resolution 3D…