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Hittade 2 uppsatser som matchar ovanstående sökkriterier.

1. 1. Error detection in blood work : Acomparison of self-supervised deep learning-based models

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Paul Vinell; [2022]
   Nyckelord :anomaly detection; outlier detection; error detection; machine learning; deep learning; blood work; blood tests; felupptäckning; extremvärden; maskininlärning; djupinlärning; blodprov;

   Sammanfattning : Errors in medical testing may cause serious problems that has the potential to severely hurt patients. There are many machine learning methods to discover such errors. However, due to the rarity of errors, it is difficult to collect enough examples to learn from them. It is therefore important to focus on methods that do not require human labeling. LÄS MER

3. 2. One-shot learning through generalized representations with neural networks

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Paul Vinell; Adam Wiker; [2020]
   Nyckelord :;

   Sammanfattning : Despite the rapid progress in the field of machine learning and artificial neural networks, many hurdles yet remain before machines can match human capabilities. One such hurdle is the copious amount of data required for these learning machines to reach adequate performance. LÄS MER