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	Referat konferencyjny 2025 Wojciech Dąbrowicki, Andrzej Rusiecki, Łukasz Jeleń, Med-Agent: a hybrid AI agent for multimodal cancer diagnosis. W: 29th International Conference on Knowledge Based and Intelligent information and Engineering Systems (KES 2025) / ed. Jonathan Flearmoy. Amsterdam : Elsevier, cop. 2025. s. 3290-3299. Zasoby:DOIURLSFX
2	Referat konferencyjny 2025 Karolina Łęcka, Andrzej Rusiecki, Universal deepfake detection across various image generators based on data from diffusion models. W: Computational Science – ICCS 2025 Workshops : 25th International Conference, Singapore, Singapore, July 7-9, 2025 : Proceedings. Pt. 3 / eds. Maciej Paszynski, Amanda S. Barnard, Yongjie Jessica Zhang. Cham : Springer Nature Switzerland AG, cop. 2025. s. 97-110. ISBN: 978-3-031-97563-9; 978-3-031-97564-6 Zasoby:DOISFX
3	Artykuł 2025 Betelhem Wubineh, Andrzej Rusiecki, Krzysztof Halawa, SE-DeepLabV3+: cervical cell segmentation and classification using a novel SE-based DeepLabV3+ and ensemble method. IEEE Access. 2025, vol. 13, s. 116430-116441. ISSN: 2169-3536 Zasoby:DOIURLSFX
4	Referat konferencyjny 2025 Betelhem Wubineh, Andrzej Rusiecki, Krzysztof Halawa, ViT-SE_Res: a hybrid vision transformer and ResNet50V2 with squeeze-and-excitation block for cervical cell classification. W: Computational Science – ICCS 2025 Workshops : 25th International Conference, Singapore, Singapore, July 7-9, 2025 : Proceedings. Pt. 2 / eds. Maciej Paszynski, Amanda S. Barnard, Yongjie Jessica Zhang. Cham : Springer Nature Switzerland AG, cop. 2025. s. 11-23. ISBN: 978-3-031-97556-1; 978-3-031-97557-8 Zasoby:DOIURLSFX
5	Artykuł 2025 Betelhem Wubineh, Andrzej Rusiecki, Krzysztof Halawa, SPP-SegNet and SE-DenseNet201: a dual-model approach for cervical cell segmentation and classification. Cancers. 2025, vol. 17, nr 13, art. 2177, s. 1-13. ISSN: 2072-6694 Zasoby:DOIURLSFX
6	Artykuł 2025 Betelhem Wubineh, Andrzej Rusiecki, Krzysztof Halawa, A systematic review of effective data augmentation in cervical cancer detection. International Journal of Electronics and Telecommunications. 2025, vol. 71, nr 2, s. 369-377. ISSN: 2300-1933 Zasoby:DOIURLSFX
7	Referat konferencyjny 2025 Betelhem Wubineh, Andrzej Rusiecki, Krzysztof Halawa, Enhancing cervical cell classification with DenseNet201 and spatial attention mechanism. W: Advances in Dependable Systems and Networks : Proceedings of the Twentieth International Conference on Dependability of Computer Systems DepCoS-RELCOMEX, June 30 – July 3, 2025, Brunów, Poland / eds. Wojciech Zamojski [i in.]. Cham : Springer Nature Switzerland AG, cop. 2025. s. 229-236. ISBN: 978-3-031-92733-1; 978-3-031-92734-8 Zasoby:DOIURLSFX
8	Referat konferencyjny 2025 Łukasz Jeleń, Krzysztof Krupka, Andrzej Rusiecki, Dynamic infrared thermography and machine learning for advanced diagnostic applications in biomedical imaging. W: Advances in Dependable Systems and Networks : Proceedings of the Twentieth International Conference on Dependability of Computer Systems DepCoS-RELCOMEX, June 30 – July 3, 2025, Brunów, Poland / eds. Wojciech Zamojski [i in.]. Cham : Springer Nature Switzerland AG, cop. 2025. s. 75-84. ISBN: 978-3-031-92733-1; 978-3-031-92734-8 Zasoby:DOIURLSFX
9	Referat konferencyjny 2025 Betelhem Wubineh, Łukasz Jeleń, Andrzej Rusiecki, 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. Zasoby:DOIURLSFX
10	Referat konferencyjny 2024 Betelhem Wubineh, Andrzej Rusiecki, Krzysztof Halawa, 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 Zasoby:DOIURL

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