Matches in SemOpenAlex for { <https://semopenalex.org/work/W3204177259> ?p ?o ?g. }
Showing items 1 to 88 of
88
with 100 items per page.
- W3204177259 endingPage "29" @default.
- W3204177259 startingPage "15" @default.
- W3204177259 abstract "We propose an optimized U-Net architecture for a brain tumor segmentation task in the BraTS21 challenge. To find the optimal model architecture and the learning schedule, we have run an extensive ablation study to test: deep supervision loss, Focal loss, decoder attention, drop block, and residual connections. Additionally, we have searched for the optimal depth of the U-Net encoder, number of convolutional channels and post-processing strategy. Our method won the validation phase and took third place in the test phase. We have open-sourced the code to reproduce our BraTS21 submission at the NVIDIA Deep Learning Examples GitHub Repository ( https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/Segmentation/nnUNet/notebooks/BraTS21.ipynb )." @default.
- W3204177259 created "2021-10-11" @default.
- W3204177259 creator A5007356288 @default.
- W3204177259 creator A5036823223 @default.
- W3204177259 creator A5059710857 @default.
- W3204177259 creator A5079642629 @default.
- W3204177259 date "2022-01-01" @default.
- W3204177259 modified "2023-10-18" @default.
- W3204177259 title "Optimized U-Net for Brain Tumor Segmentation" @default.
- W3204177259 cites W1641498739 @default.
- W3204177259 cites W1677182931 @default.
- W3204177259 cites W1901129140 @default.
- W3204177259 cites W2056753605 @default.
- W3204177259 cites W2117539524 @default.
- W3204177259 cites W2194775991 @default.
- W3204177259 cites W2604468722 @default.
- W3204177259 cites W2604785265 @default.
- W3204177259 cites W2751069891 @default.
- W3204177259 cites W2884436604 @default.
- W3204177259 cites W2962914239 @default.
- W3204177259 cites W2963046541 @default.
- W3204177259 cites W2963351448 @default.
- W3204177259 cites W2963446712 @default.
- W3204177259 cites W3028279406 @default.
- W3204177259 cites W3112701542 @default.
- W3204177259 cites W3142164167 @default.
- W3204177259 cites W4212875960 @default.
- W3204177259 doi "https://doi.org/10.1007/978-3-031-09002-8_2" @default.
- W3204177259 hasPublicationYear "2022" @default.
- W3204177259 type Work @default.
- W3204177259 sameAs 3204177259 @default.
- W3204177259 citedByCount "18" @default.
- W3204177259 countsByYear W32041772592022 @default.
- W3204177259 countsByYear W32041772592023 @default.
- W3204177259 crossrefType "book-chapter" @default.
- W3204177259 hasAuthorship W3204177259A5007356288 @default.
- W3204177259 hasAuthorship W3204177259A5036823223 @default.
- W3204177259 hasAuthorship W3204177259A5059710857 @default.
- W3204177259 hasAuthorship W3204177259A5079642629 @default.
- W3204177259 hasBestOaLocation W32041772592 @default.
- W3204177259 hasConcept C108583219 @default.
- W3204177259 hasConcept C111919701 @default.
- W3204177259 hasConcept C11413529 @default.
- W3204177259 hasConcept C118505674 @default.
- W3204177259 hasConcept C154945302 @default.
- W3204177259 hasConcept C155512373 @default.
- W3204177259 hasConcept C173608175 @default.
- W3204177259 hasConcept C177264268 @default.
- W3204177259 hasConcept C199360897 @default.
- W3204177259 hasConcept C2776760102 @default.
- W3204177259 hasConcept C41008148 @default.
- W3204177259 hasConcept C43126263 @default.
- W3204177259 hasConcept C68387754 @default.
- W3204177259 hasConcept C89600930 @default.
- W3204177259 hasConceptScore W3204177259C108583219 @default.
- W3204177259 hasConceptScore W3204177259C111919701 @default.
- W3204177259 hasConceptScore W3204177259C11413529 @default.
- W3204177259 hasConceptScore W3204177259C118505674 @default.
- W3204177259 hasConceptScore W3204177259C154945302 @default.
- W3204177259 hasConceptScore W3204177259C155512373 @default.
- W3204177259 hasConceptScore W3204177259C173608175 @default.
- W3204177259 hasConceptScore W3204177259C177264268 @default.
- W3204177259 hasConceptScore W3204177259C199360897 @default.
- W3204177259 hasConceptScore W3204177259C2776760102 @default.
- W3204177259 hasConceptScore W3204177259C41008148 @default.
- W3204177259 hasConceptScore W3204177259C43126263 @default.
- W3204177259 hasConceptScore W3204177259C68387754 @default.
- W3204177259 hasConceptScore W3204177259C89600930 @default.
- W3204177259 hasLocation W32041772591 @default.
- W3204177259 hasLocation W32041772592 @default.
- W3204177259 hasOpenAccess W3204177259 @default.
- W3204177259 hasPrimaryLocation W32041772591 @default.
- W3204177259 hasRelatedWork W2790662084 @default.
- W3204177259 hasRelatedWork W2948658236 @default.
- W3204177259 hasRelatedWork W2960184797 @default.
- W3204177259 hasRelatedWork W4200477060 @default.
- W3204177259 hasRelatedWork W4220708658 @default.
- W3204177259 hasRelatedWork W4220855245 @default.
- W3204177259 hasRelatedWork W4243168368 @default.
- W3204177259 hasRelatedWork W4285827401 @default.
- W3204177259 hasRelatedWork W4293211451 @default.
- W3204177259 hasRelatedWork W4295036012 @default.
- W3204177259 isParatext "false" @default.
- W3204177259 isRetracted "false" @default.
- W3204177259 magId "3204177259" @default.
- W3204177259 workType "book-chapter" @default.