Expansion Rate Parametrization and K-Fold Based Inference with U-Net Neural Networks for Multiclass Medical Image Segmentation

Roman Statkevych, Yuri G. Gordienko, Sergii G. Stirenko. Expansion Rate Parametrization and K-Fold Based Inference with U-Net Neural Networks for Multiclass Medical Image Segmentation. In Leszek Rutkowski, Rafal Scherer, Marcin Korytkowski, Witold Pedrycz, Ryszard Tadeusiewicz, Jacek M. Zurada, editors, Artificial Intelligence and Soft Computing - 22nd International Conference, ICAISC 2023, Zakopane, Poland, June 18-22, 2023, Proceedings, Part I. Volume 14125 of Lecture Notes in Computer Science, pages 251-262, Springer, 2023. [doi]

@inproceedings{StatkevychGS23,
  title = {Expansion Rate Parametrization and K-Fold Based Inference with U-Net Neural Networks for Multiclass Medical Image Segmentation},
  author = {Roman Statkevych and Yuri G. Gordienko and Sergii G. Stirenko},
  year = {2023},
  doi = {10.1007/978-3-031-42505-9_22},
  url = {https://doi.org/10.1007/978-3-031-42505-9_22},
  researchr = {https://researchr.org/publication/StatkevychGS23},
  cites = {0},
  citedby = {0},
  pages = {251-262},
  booktitle = {Artificial Intelligence and Soft Computing - 22nd International Conference, ICAISC 2023, Zakopane, Poland, June 18-22, 2023, Proceedings, Part I},
  editor = {Leszek Rutkowski and Rafal Scherer and Marcin Korytkowski and Witold Pedrycz and Ryszard Tadeusiewicz and Jacek M. Zurada},
  volume = {14125},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-031-42505-9},
}