Sökning: "confidence annotation"

Hittade 4 avhandlingar innehållade orden confidence annotation.

  1. 1. Information state based speech recognition

    Författare :Rebecca Jonson; Göteborgs universitet; []
    Nyckelord :HUMANIORA; HUMANITIES; dialogue systems; speech recognition; language modelling; dialogue move; dialogue context; ASR; higher level knowledge; linguistic knowledge; N-Best re-ranking; confidence scoring; confidence annotation; information state; ISU approach;

    Sammanfattning : One of the pitfalls in spoken dialogue systems is the brittleness of automatic speech recognition (ASR). ASR systems often misrecognize user input and they are unreliable when it comes to judging their own performance. LÄS MER

  3. 2. Genomics and bioinformatics approaches to functional gene annotation

    Författare :Danielle Kemmer; Karolinska Institutet; Karolinska Institutet; []
    Nyckelord :;

    Sammanfattning : Biomedical research has been undergoing a quasi-revolution with the dawn of the genomics era. The flood of sequence data from the various genome projects, the task of cataloging the entire coding portion of a genome instead of identifying and characterizing individual genes, as well as technical demands accompanying these developments have posed great challenges to the research community. LÄS MER

  4. 3. Assignment and assessment of orthology and gene function

    Författare :Christian Storm; Karolinska Institutet; Karolinska Institutet; []
    Nyckelord :Orthology; paralogy; homology; bootstrap; tree reconciliation; Pfam; functional annotation;

    Sammanfattning : Several genomes from different species have been sequenced over the last years, most notably the human genome. An important task of computational biology is to classify and functionally annotate the large amount of sequence data created by the genome sequencing projects. LÄS MER

  5. 4. Generalisation and reliability of deep learning for digital pathology in a clinical setting

    Författare :Milda Pocevičiūtė; Claes Lundström; Stina Garvin; Gabriel Eilertsen; Nasir Rajpoot; Linköpings universitet; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Deep learning; Digital pathology; Generalisation; Uncertainty estimation; Anomaly detection; Data distribution shift;

    Sammanfattning : Deep learning (DL) is a subfield of artificial intelligence (AI) focused on developing algorithms that learn from data to perform some tasks that can aid humans in their daily life or work assignments. Research demonstrates the potential of DL in supporting pathologists with routine tasks like detecting breast cancer metastases and grading prostate cancer. LÄS MER