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research_group:publications [2020/10/22 15:05]
pkleczek [2020]
research_group:publications [2023/12/27 22:07]
macal
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   * [[https://​bpp.agh.edu.pl/​autor/​piekarski-michal-43242|Michał Piekarski]]   * [[https://​bpp.agh.edu.pl/​autor/​piekarski-michal-43242|Michał Piekarski]]
  
-MVG Group IF: 25.7\\+MVG Group IF: 25.7\\ ​FIXME zaktualizować 
 + 
 +===== 2023 ===== 
 +  * **Aleksandrowicz M.** and **Jaworek-Korjakowska J.**: //Metrics for Assessing Generalization of Deep Reinforcement Learning in Parameterized Environments//,​ Journal of Artificial Intelligence and Soft Computing Research, 2023, **IF 2,8, 140 pkt**, [[https://​doi.org/​10.2478/​jaiscr-2024-0003]] 
 + 
 +===== 2022 ===== 
 + 
 +  * Cassidy B., Kendrick C., **Brodzicki A.**, **Jaworek-Korjakowska J.**, Hoon Yap M.: Analysis of the ISIC image datasets: usage, benchmarks and recommendations,​ Medical Image Analysis, 2022, **IF 8.545, 200 pkt** 
 + 
 +  * **Wójcicka A.**, Walusiak Ł., Mroczka K., **Jaworek-Korjakowska J.**, Oprzędkiewicz K., Wróbel Z.: The object segmentation from the microstructure of a FSW dissimilar weld, Materials, 2022, **IF 3,748, 140 pkt** 
 + 
 +  * **Brodzicki A.**, **Kucharski D.**, **Piekarski M.**, **Kostuch A.**, **Jaworek-Korjakowska J.**: Deep neural network interpretability methods for supervised and unsupervised problems, PP-RAI'​2022:​ proceedings of the 3rd Polish conference on Artificial intelligence,​ 2022 
 + 
 +  * Gorgoń M., et al.: Systemy wizyjne w zastosowaniach przemysłowych,​ Nauka – technika – technologia : seria wydawnicza AGH, 2022 
 + 
 +  * **Piekarski M.**: Deep Neural Network for Beam Profile Classification in Synchrotron,​ International Beam Instrumentation Conference, 2022 
 + 
 +  * **Kucharski D.**, **Kostuch A.**, **Brodzicki A.**, **Noworolnik F.**, **Jaworek-Korjakowska J.**: DFU-Ens: End-to-End Diabetic Foot Ulcer Segmentation Framework with Vision Transformer Based Detection, Proceedings of the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022 
 + 
 +  * **Jaworek-Korjakowska,​ J.**, **Wójcicka A.**, **Kucharski D.**, **Brodzicki A.**, Kendrick C., Cassidy B., Hoon Yap M.: Skin_Hair dataset: Setting the benchmark for effective hair inpainting methods for improving the image quality of dermoscopic images, Proceedings of the 2022 European Conference on Computer Vision (ECCV), 2022 
 + 
 + 
 +===== 2021 ===== 
 + 
 +  * **Jaworek-Korjakowska J.**, **Kostuch A.**, Skruch P.: SafeSO: interpretable and explainable deep learning approach for seat occupancy classification in vehicle interior, 2021 IEEE/CVF conference on Computer Vision and Pattern Recognition Workshops, 2021 
 + 
 +  * **Brodzicki A.**, **Piekarski M.**, **Jaworek-Korjakowska J.**: The whale optimization algorithm approach for deep neural networks, Sensors, 2021, IF 3,847, 100 pkt 
 + 
 +  * **Jaworek-Korjakowska J.**, **Brodzicki A.**, Cassidy B., Kendrick C., Hoon Yap M.: Interpretability of a deep learning based approach for the classification of skin lesions into main anatomic body sites, Cancers, 2021, IF 6.575, 140 pkt 
  
 ===== 2020 ===== ===== 2020 =====
  
-  * (In Press) **Michał Piekarski**,​ **Joanna Jaworek-Korjakowska**,​ Adriana I. Wawrzyniak, **Marek Gorgon**, Convolutional neural network architecture for beam instabilities identification in Synchrotron Radiation Systems as an anomaly detection problem, Measurement,​ 2020, [[https://​doi.org/​10.1016/​j.measurement.2020.108116]] \\ [size=80%][IF5 (2018) = 3.364, Top10][/​size] ​+  * **Andrzej Brodzicki**,​ **Joanna Jaworek-Korjakowska**,​ **Paweł Kłeczek**, Megan Garland, Matthew Bogyo. //​Pre-trained deep convolutional neural network for clostridioides difficile bacteria cytotoxicity classification based on fluorescence images//, Sensors, 20(23), 2020, [[https://​doi.org/​10.3390/​s20236713|10.3390/​s20236713]] ([[https://​www.mdpi.com/​1424-8220/​20/​23/​6713|HTML]]) \\ [size=80%][IF5 (2018) = ???][/size]  
 + 
 +  * **Michał Piekarski**,​ **Joanna Jaworek-Korjakowska**,​ Adriana I. Wawrzyniak, **Marek Gorgon**, Convolutional neural network architecture for beam instabilities identification in Synchrotron Radiation Systems as an anomaly detection problem, Measurement,​ 2020, [[https://​doi.org/​10.1016/​j.measurement.2020.108116]] \\ [size=80%][IF5 (2018) = 3.364, Top10][/​size] ​
  
   * **Dariusz Kucharski**,​ **Pawel Kleczek**, **Joanna Jaworek-Korjakowska**,​ Grzegorz Dyduch, **Marek Gorgon**. //​Semi-Supervised Nests of Melanocytes Segmentation Method Using Convolutional Autoencoders//​. Sensors, 2020, vol. 20, issue 6, 1546, doi: [[https://​doi.org/​10.3390/​s20061546|10.3390/​s20061546]] ​ ([[https://​www.mdpi.com/​1424-8220/​20/​6/​1546/​htm|HTML]]) ​ \\ [size=80%][IF (2019): 3.275; IF5 (2018) = 2.737, Top10][/​size] ​   * **Dariusz Kucharski**,​ **Pawel Kleczek**, **Joanna Jaworek-Korjakowska**,​ Grzegorz Dyduch, **Marek Gorgon**. //​Semi-Supervised Nests of Melanocytes Segmentation Method Using Convolutional Autoencoders//​. Sensors, 2020, vol. 20, issue 6, 1546, doi: [[https://​doi.org/​10.3390/​s20061546|10.3390/​s20061546]] ​ ([[https://​www.mdpi.com/​1424-8220/​20/​6/​1546/​htm|HTML]]) ​ \\ [size=80%][IF (2019): 3.275; IF5 (2018) = 2.737, Top10][/​size] ​
  
-  * **Joanna Jaworek-Korjakowska**,​ **Pawel Kleczek**, **Marek Gorgon**. //Melanoma Thickness Prediction Based on Convolutional Neural Network With VGG-19 Model Transfer Learning//. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Long Beach, CA, USA, 2019, pp. 2748--2756, doi: [[https://​doi.org/​10.1109/​CVPRW.2019.00333]].+  * **Joanna Jaworek-Korjakowska**,​ **Pawel Kleczek**, **Marek Gorgon**. //Melanoma Thickness Prediction Based on Convolutional Neural Network With VGG-19 Model Transfer Learning//. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Long Beach, CA, USA, 2019, pp. 2748--2756, doi: [[https://​doi.org/​10.1109/​CVPRW.2019.00333]] ​\\ [size=80%][Honorable Mention Award; 200 pkt MNiSW][/​size]
  
  
research_group/publications.txt · Last modified: 2023/12/27 22:09 by macal