E-mail: andrzej.rusiecki@pwr.edu.pl

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

ul. Z. Janiszewskiego 11/17, 50-372 Wrocław
building C-3, room 230
phone +48 71 320 4226

Research fields

• Deep learning; artificial neural networks; learning algorithms; image processing; robust statistics.

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Recent papers

2016

• Kordos M., Rusiecki A., Reducing noise impact on MLP training. Soft Computing. 2016, vol. 20, nr 1, s. 49-65.
• Halawa K., Bazan M., Ciskowski P., Janiczek T., Kozaczewski P., Rusiecki A., Road traffic predictions across major city intersections using multilayer perceptrons and data from multiple intersections located in various places. IET Intelligent Transport Systems. 2016, vol. 10, nr 7, s. 469-475.

2015

• Rusiecki A., Kordos M., Effectiveness of unsupervised training in deep learning neural networks. Schedae Informaticae. 2015, vol. 24, s. 1-10.
• Bazan M., Bożek M., Ciskowski P., Halawa K., Janiczek T., Kozaczewski P., Rusiecki A., Some acpects of Intelligent Transport System auditing. Archives of Transport System Telematics. 2015, vol. 8, nr 3, s. 3-8.

2014

• Rusiecki A., Kordos M., Kamiński T., Greń K., Training neural networks on noisy data. W: Artificial intelligence and soft computing: 13th International Conference, ICAISC 2014, Zakopane, Poland, June 1-5, 2014: proceedings. Pt. 1 / Leszek Rutkowski [i in.] (eds.). Cham [i in.]: Springer, cop. 2014. s. 131-142 (Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence, ISSN 0302-9743; vol. 8467).

2013

• Rusiecki A., Robust learning algorithm based on LTA estimator. Neurocomputing. 2013, vol. 120, s. 624-632.

2012

• Rusiecki A., Robust learning algorithm based on iterative least median of squares. Neural Processing Letters. 2012, vol. 36, nr 2, s. 145-160.

Papers in DONA database

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Selected publications
1	Proceeding paper 2025 Betelhem Wubineh, DCGAN-based cytology image augmentation for cervical cancer cell classification using transfer learning. W: CENTERIS - International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2024, November 13-15, Funchal, Portugal / eds. Ricardo Martinho, Maria Manuela Cruz Cunha, Rui Rijo. Amsterdam : Elsevier, cop. 2025. s. 1003-1011. Resources:DOIURLSFX
2	Proceeding paper 2024 Betelhem Wubineh, Cervical cell segmentation and classification using U-Net and hybrid VGG19-AlexNet architecture. W: 2024 International Conference on Information and Communication Technology for Development for Africa (ICT4DA), Bahir Dar, Ethiopia, November 18-20, 2024 / eds. Esubalew Alemneh, Fisseha Mekuria, Ethiopia Nigussie. Danvers, MA : IEEE, cop. 2024. s. 37-42. ISBN: 979-8-3315-2780-8; 979-8-3315-2779-2 Resources:DOIURL
3	Proceeding paper 2024 Marcin Tarasiuk, Dariusz Olearczuk, Machine learning-enhanced turfgrass logistics through remote sensing. W: 11th Carpathian Logistics Congress - CLC 2023, November 8-10, 2023, Prague, Czech Republic : conference proceedings. Ostrava : TANGER Ltd., cop. 2024. s. 155-160. ISBN: 978-80-88365-17-4 Resources:DOI
4	Proceeding paper 2024 Jakub Kędzierski, Deep learning approach to improve image super-resolution with aliasing. W: 28th International Conference on Knowledge Based and Intelligent information and Engineering Systems (KES 2024) / ed. Jonathan Flearmoy. Amsterdam : Elsevier, cop. 2024. s. 1250-1259. Resources:DOIURLSFX
5	Article 2024 Adam Radkowski, Paweł Więcek, Wykorzystanie teledetekcji i uczenia maszynowego do oceny stanu terenów zielonych. Przegląd Budowlany. 2024, nr 5, s. 187-191. ISSN: 0033-2038 Resources:DOIURL
6	Article 2024 Betelhem Wubineh, Classification of cervical cells from the Pap smear image using the RES_DCGAN data augmentation and ResNet50V2 with self-attention architecture. Neural Computing & Applications. 2024, vol. 36, s. 21801-21815. ISSN: 0941-0643; 1433-3058 Resources:DOIURLSFX
7	Article 2024 Betelhem Wubineh, Segmentation and classification techniques for pap smear images in detecting cervical cancer: a systematic review. IEEE Access. 2024, vol. 12, s. 118195-118213. ISSN: 2169-3536 Resources:DOIURLSFX
8	Proceeding paper 2024 Maciej Wilhelmi, Simple CNN as an alternative for large pretrained models for medical image classification - MedMNIST case study. W: CENTERIS – International Conference on ENTERprise Information Systems / ProjMAN - International Conference on Project MANagement / HCist - International Conference on Health and Social Care Information Systems and Technologies 2023, November 8-10, Porto, Portugal / eds. Ricardo Filipe Gonçalves Martinho, Maria Manuela Cruz da Cunha. Amsterdam : Elsevier, cop. 2024. s. 1298-1303. Resources:DOIURLSFX
9	Proceeding paper 2024 Betelhem Wubineh, Segmentation of cytology images to detect cervical cancer using deep learning techniques. W: Computational Science - ICCS 2024 : 24th International Conference, Malaga, Spain, July 2-4, 2024 : Proceedings. Pt. 4 / eds. Leonardo Franco [i in.]. Cham : Springer, cop. 2024. s. 270-278. ISBN: 978-3-031-63771-1; 978-3-031-63772-8 Resources:DOIURLSFX
10	Proceeding paper 2024 Betelhem Wubineh, Data augmentation techniques to detect cervical cancer using deep learning: a systematic review. W: System Dependability - Theory and Applications : Proceedings of the Nineteenth International Conference on Dependability of Computer Systems DepCoS-RELCOMEX, July 1-5, 2024, Brunów, Poland / eds. Wojciech Zamojski [i in.]. Cham : Springer, cop. 2024. s. 325-336. ISBN: 978-3-031-61856-7; 978-3-031-61857-4 Resources:DOIURLSFX

All publications