Adam Pardyl

According to our database, Adam Pardyl authored at least 8 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale.

Adam Pardyl, Michal Wronka, Maciej Wolczyk, Kamil Adamczewski, Tomasz Trzcinski, Bartosz Zielinski

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers.

Adam Pardyl, Grzegorz Kurzejamski, Jan Olszewski, Tomasz Trzcinski, Bartosz Zielinski

CoRR, 2023

Active Visual Exploration Based on Attention-Map Entropy.

Adam Pardyl, Grzegorz Rypesc, Grzegorz Kurzejamski, Bartosz Zielinski, Tomasz Trzcinski

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

CompLung: Comprehensive Computer-Aided Diagnosis of Lung Cancer.

Adam Pardyl, Dawid Rymarczyk, Joanna Jaworek-Korjakowska, Dariusz Kucharski, Andrzej Brodzicki, Julia Lasek, Zofia Schneider, Iwona Kucybala, Andrzej Urbanik, Rafal Obuchowicz, Zbislaw Tabor, Bartosz Zielinski

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

ProPML: Probability Partial Multi-label Learning.

Lukasz Struski, Adam Pardyl, Jacek Tabor, Bartosz Zielinski

Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

2022

ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification.

Dawid Rymarczyk, Adam Pardyl, Jaroslaw Kraus, Aneta Kaczynska, Marek Skomorowski, Bartosz Zielinski

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Automating Patient-Level Lung Cancer Diagnosis in Different Data Regimes.

Adam Pardyl, Dawid Rymarczyk, Zbislaw Tabor, Bartosz Zielinski

Proceedings of the Neural Information Processing - 29th International Conference, 2022

2021

ProtoMIL: Multiple Instance Learning with Prototypical Parts for Fine-Grained Interpretability.

Dawid Rymarczyk, Aneta Kaczynska, Jaroslaw Kraus, Adam Pardyl, Bartosz Zielinski

CoRR, 2021