Sign in

 

Faculty of Information and Communication Technology

Łukasz Jeleń, PhD

E-mail: lukasz.jelen@pwr.edu.pl

Unit: Faculty of Information and Communication Technology (N) » Department of Computer Engineering

ul. Z. Janiszewskiego 11/17, Wrocław, Poland
C-3 building, office: 230
tel. 71 320 4226


Research interests:

  • Computer Vision, Pattern Recognition, Computer Aided Diagnosis, Biomedical Image Processing

Recent papers:

2020

Łukasz Jeleń Texture Description for Classification of Fine Needle Aspirates. In: Korbicz J., Maniewski R., Patan K., Kowal M. (eds) Current Trends in Biomedical Engineering and Bioimages Analysis. PCBEE 2019. Advances in Intelligent Systems and Computing, vol 1033. Springer, Cham. https://doi.org/10.1007/978-3-030-29885-2_10

Adrian Banachowicz, Anna Lis-Nawara, Michał Jeleń, Łukasz Jeleń
Convolutional Neural Networks for Dot Counting in Fluorescence in Situ Hybridization Imaging. In: Zamojski W., Mazurkiewicz J., Sugier J., Walkowiak T., Kacprzyk J. (eds) Theory and Applications of Dependable Computer Systems. DepCoS-RELCOMEX 2020. Advances in Intelligent Systems and Computing, vol 1173. Springer, Cham. https://doi.org/10.1007/978-3-030-48256-5_309

2018

Łukasz Jeleń, Michał Kulus, Tomasz Jurek
Pattern Recognition Framework for Histological Slide Segmentation. In: Saeed K., Homenda W. (eds) Computer Information Systems and Industrial Management. CISIM 2018. Lecture Notes in Computer Science, vol 11127. Springer, Cham. https://doi.org/10.1007/978-3-319-99954-8_4

2017

Muneera Alsaedi, Thomas Fevens, Adam Krzyżak, Łukasz Jeleń
Cytological malignancy grading system for fine needle aspiration biopsies of breast cancer. In: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2017) : proceedings, Kansas City, MO, USA, Nov 13-16, 2017 / eds. Xiaohua Hu [i in.]. Danvers, MA : IEEE, cop. 2017. s. 705-709

2016

Bartosz Krawczyk, Mikel Galar, Łukasz Jeleń, Francisco Herrera
Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy. Applied Soft Computing. 2016, vol. 38, s. 714-726.

Łukasz Jeleń, Adam Krzyżak, Thomas Fevens, Michał Jeleń
Influence of feature set reduction on breast cancer malignancy classification of fine needle aspiration biopsies. Computers in Biology and Medicine. 2016, vol. 79, s. 80-91.

 

Full publication list


Selected publications
1
Article
2023
Adam Radkowski, Iwona Radkowska, Karol Wolski, Henryk Bujak, Łukasz Jeleń,
The influence of the multi-component mineral-organic concentrate on the bonitation value of turfgrass. Agronomy (Basel). 2023, vol. 13, nr 3, art. 855, s. 1-12. ISSN: 2073-4395
Resources:DOIURLSFXImpact FactorMaster Journal ListMinistry of Science and Higher Education Journal ListOpen Access
2
Proceeding paper
2022
Łukasz Jeleń, Marek Karkula, Dariusz Olearczuk,
A computer vision-based approach for storage locations occupancy detection using deep learning. W: 10th Carpathian Logistics Congress - CLC 2022, Jun 15 - 17, 2022, Bojnice, Slovakia : conference proceedings. Ostrava : TANGER Ltd., cop. 2022. s. 73-79. ISBN: 978-80-88365-08-2
Resources:URLOpen Access
3
Proceeding paper
2022
Marta I Emirsajłow, Łukasz Jeleń,
Analysis of effectiveness of selected classifiers for recognizing psychological patterns. W: Proceedings of Sixth International Congress on Information and Communication Technology, ICICT 2021, London. Vol. 2 /eds. Xin-She Yang [i in.]. Singapore : Springer, cop. 2022. s. 511-521. ISBN: 978-981-16-2379-0; 978-981-16-2380-6
Resources:DOIURLSFX
4
Proceeding paper
2021
Mikołaj Skubisz, Łukasz Jeleń,
Deep learning bio-signal analysis from a wearable device. W: Computer information systems and industrial management : 20th International Conference, CISIM 2021, Ełk, Poland, September 24–26, 2021 : proceedings / eds. Khalid Saeed, Jiří Dvorský. Cham : Springer, cop. 2021. s. 343-353. ISBN: 978-3-030-84339-7; 978-3-030-84340-3
Resources:DOIURLSFX
5
Proceeding paper
2020
Anita Rybiałek, Łukasz Jeleń,
Application of denseNets for classification of breast cancer mammograms. W: Computer information systems and industrial management : 19th International Conference, CISIM 2020, Bialystok, Poland, October 16–18, 2020 : proceedings / eds. Khalid Saeed, Jiří Dvorský. Switzerland : Springer, cop. 2020. s. 266-277. ISBN: 978-3-030-47678-6; 978-3-030-47679-3
Resources:DOISFX
6
Proceeding paper
2020
Adrian Banachowicz, Anna Lis-Nawara, Michał Jeleń, Łukasz Jeleń,
Convolutional neural networks for dot counting in fluorescence in situ hybridization imaging. W: Theory and Applications of Dependable Computer Systems : proceedings of the Fifteenth International Conference on Dependability of Computer Systems DepCoS-RELCOMEX, June 29 - July 3, 2020, Brunów, Poland / eds. Wojciech Zamojski [i in.]. Cham : Springer, cop. 2020. s. 21-30. ISBN: 978-3-030-48255-8; 978-3-030-48256-5
Resources:DOISFX
7
Proceeding paper
2020
Łukasz Jeleń,
Texture description for classification of fine needle aspirates. W: Current Trends in Biomedical Engineering and Bioimages Analysis : Proceedings of the 21st Polish Conference on Biocybernetics and Biomedical Engineering / eds. Józef Korbicz [i in.]. Switzerland : Springer, cop. 2020. s. 107-116. ISBN: 978-3-030-29885-2; 978-3-030-29884-5
Resources:DOIURLSFX
8
Proceeding paper
2018
Bartosz Miselis, Michał Kulus, Tomasz Jurek, Andrzej Rusiecki, Łukasz Jeleń,
Deep neural network for whole slide vein segmentation. W: Computer Information Systems and Industrial Management : 17th International Conference, CISIM 2018, Olomouc, Czech Republic, September 27-29, 2018 : proceedings / eds. Khalid Saeed, Władysław Homenda. [Cham] : Springer, cop. 2018. s. 57–67. ISBN: 978-3-319-99953-1
Resources:DOISFXWeb of Science CC
9
Proceeding paper
2018
Łukasz Jeleń, Michał Kulus, Tomasz Jurek,
Pattern recognition framework for histological slide segmentation. W: Computer Information Systems and Industrial Management : 17th International Conference, CISIM 2018, Olomouc, Czech Republic, September 27-29, 2018 : proceedings / eds. Khalid Saeed, Władysław Homenda. [Cham] : Springer, cop. 2018. s. 37-45. ISBN: 978-3-319-99953-1
Resources:DOISFXWeb of Science CC
10
Proceeding paper
2018
Muneera Alsaedi, Thomas Fevens, Adam Krzyżak, Łukasz Jeleń,
Hybrid RUSBoost versus data sampling to address data imbalance for breast cancer cytological malignancy grading. W: Proceedings of the International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI 2018), Montreal, Canada, May 13-17, 2018. [B.m.] : CENPARMI, 2018. s. 545-551. ISBN: 1-895193-06-0

All publications

Politechnika Wrocławska © 2024