Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Majchrowska, Sylwia"'
Supervised training of deep learning models for medical imaging applications requires a significant amount of labeled data. This is posing a challenge as the images are required to be annotated by medical professionals. To address this limitation, we
Externí odkaz:
http://arxiv.org/abs/2309.11899
Autor:
Ferlin, Maria, Majchrowska, Sylwia, Plantykow, Marta, Kwaśniwska, Alicja, Mikołajczyk-Bareła, Agnieszka, Olech, Milena, Nalepa, Jakub
Labeling is the cornerstone of supervised machine learning, which has been exploited in a plethora of various applications, with sign language recognition being one of them. However, such algorithms must be fed with a huge amount of consistently labe
Externí odkaz:
http://arxiv.org/abs/2302.10768
Autor:
Limeros, Sandra Carrasco, Majchrowska, Sylwia, Johnander, Joakim, Petersson, Christoffer, Llorca, David Fernández
Motion prediction systems aim to capture the future behavior of traffic scenarios enabling autonomous vehicles to perform safe and efficient planning. The evolution of these scenarios is highly uncertain and depends on the interactions of agents with
Externí odkaz:
http://arxiv.org/abs/2212.03806
Autor:
Limeros, Sandra Carrasco, Majchrowska, Sylwia, Johnander, Joakim, Petersson, Christoffer, Sotelo, Miguel Ángel, Llorca, David Fernández
Publikováno v:
CAAI Transactions on Intelligence Technology 24686557 (ISSN) 24682322 (eISSN) 2023
Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning. This task is very complex, as the behaviour of road agents depends on many factors and the number of possible future trajectories can
Externí odkaz:
http://arxiv.org/abs/2210.16144
Autor:
Limeros, Sandra Carrasco, Majchrowska, Sylwia, Zoubi, Mohamad Khir, Rosén, Anna, Suvilehto, Juulia, Sjöblom, Lisa, Kjellberg, Magnus
Publikováno v:
Digital Interaction and Machine Intelligence. MIDI 2022. Lecture Notes in Networks and Systems, vol 710. Springer, Cham
The lack of sufficiently large open medical databases is one of the biggest challenges in AI-powered healthcare. Synthetic data created using Generative Adversarial Networks (GANs) appears to be a good solution to mitigate the issues with privacy pol
Externí odkaz:
http://arxiv.org/abs/2208.11702
Publikováno v:
In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds) Medical Image Computing and Computer Assisted Intervention - MICCAI 2022. MICCAI 2022. Lecture Notes in Computer Science, vol 13438. Springer, Cham
New medical datasets are now more open to the public, allowing for better and more extensive research. Although prepared with the utmost care, new datasets might still be a source of spurious correlations that affect the learning process. Moreover, d
Externí odkaz:
http://arxiv.org/abs/2206.15182
Autor:
Stefańska, Karolina, Majchrowska, Sylwia, Gemza, Karolina, Soboń, Grzegorz, Sotor, Jarosław, Mergo, Paweł, Tarnowski, Karol, Martynkien, Tadeusz
Publikováno v:
Opt. Lett. 47(16), 4183-4186 (2022)
We report on trapped pulse generation in birefringent microstructured optical fiber. Linearly polarized fs pulses are injected into the microstructured fiber in anomalous dispersion regime. We observed experimentally that soliton pulse polarized alon
Externí odkaz:
http://arxiv.org/abs/2204.13773
This paper presents our recent developments in the automatic processing of sign language corpora using the Hamburg Sign Language Annotation System (HamNoSys). We designed an automated tool to convert HamNoSys annotations into numerical labels for def
Externí odkaz:
http://arxiv.org/abs/2204.06924
Publikováno v:
Sci Rep 12, 10583 (2022)
The statistical properties of the density map (DM) approach to counting microbiological objects on images are studied in detail. The DM is given by U$^2$-Net. Two statistical methods for deep neural networks are utilized: the bootstrap and the Monte
Externí odkaz:
http://arxiv.org/abs/2203.09474
Publikováno v:
Optics Letters Vol. 47, Issue 10, pp. 2522-2525 (2022)
This study investigated the nonlinear frequency conversions between the six polarization modes of a two-mode birefringent fiber. The aim was to demonstrate that the selective excitation of different combinations of linearly polarized spatial modes at
Externí odkaz:
http://arxiv.org/abs/2203.04654