Year 2021

• Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift

  Publication

  • S. Cygert
  • A. Czyżewski
  • B. Wróblewski
  • R. Słowiński
  • K. Woźniak

  - Year 2021

  While recent computer vision algorithms achieve impressive performance on many benchmarks, they lack robustness - presented with an image from a different distribution, (e.g. weather or lighting conditions not considered during training), they may produce an erroneous prediction. Therefore, it is desired that such a model will be able to reliably predict its confidence measure. In this work, uncertainty estimation for the task...

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Year 2020

• Deep learning for recommending subscription-limited documents

  Publication

  • G. Chłodziński
  • K. Woźniak

  - Year 2020

  Documents recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...

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