Sökning: "annotation transfer"

Visar resultat 1 - 5 av 18 uppsatser innehållade orden annotation transfer.

  1. 1. Mutual Enhancement of Environment Recognition and Semantic Segmentation in Indoor Environment

    Master-uppsats,

    Författare :Venkata Vamsi Challa; [2024]
    Nyckelord :Semantic Segmentation; Scene Classification; Environment Recognition; Machine Learning; Deep Learning; Image Classification; Vision Transformers; SAM Segment Anything Model ; Image Segmentation; Contour-aware semantic segmentation;

    Sammanfattning : Background:The dynamic field of computer vision and artificial intelligence has continually evolved, pushing the boundaries in areas like semantic segmentation andenvironmental recognition, pivotal for indoor scene analysis. This research investigates the integration of these two technologies, examining their synergy and implicayions for enhancing indoor scene understanding. LÄS MER

  3. 2. Key Sentence Extraction From CRISPR-Cas9 Articles Using Sentence Transformers

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Sandra Henningsson; Brage Stranden Lae; [2023-11-09]
    Nyckelord :NLP; Transformers; CRISPR; semantic search; keyphrase extraction;

    Sammanfattning : The annotation of CRISPR-related articles and extraction of key content has traditionally relied on manual efforts. Manual annotation is error-prone and timeconsuming. This thesis presents an alternative approach using transfer learning and pre-trained models based on the Transformer architecture. LÄS MER

  4. 3. Automatic Semantic Role Labelling (SRL) in Swedish

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Lucy Yang Buhr; [2023-10-05]
    Nyckelord :Semantic role labelling; SRL; transfer learning; multi-task learning; multilingual transfer; T5; mT5;

    Sammanfattning : In this paper, using deep learning networks, the first end-to-end semantic role labelling model (SRL) has been developed for Swedish texts. This Swedish SRL model can, with a given Swedish sentence, perform trigger identification, frame classification and argument extraction tasks automatically in a series. LÄS MER

  5. 4. Understanding the Robustnessof Self Supervised Representations

    Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Johan Rodahl Holmgren; [2023]
    Nyckelord :Self-Supervision; AI; Robustness; Computer-Vision;

    Sammanfattning : This work investigates the robustness of learned representations of self-supervised learn-ing approaches, focusing on distribution shifts in computer vision. Joint embedding architecture and method-based self-supervised learning approaches have shown advancesin learning representations in a label-free manner and efficient knowledge transfer towardreducing human annotation needs. LÄS MER

  7. 5. Multi-Scale Task Dynamics in Transfer and Multi-Task Learning : Towards Efficient Perception for Autonomous Driving

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

    Författare :Simon Ekman von Huth; [2023]
    Nyckelord :Autonomous Driving; Computer Vision; Deep Learning; Machine Learning; Multi-Task Learning; Transfer Learning; Task Relationships; Task Dynamics; Python; Multi-Scale Representation Learning; Fuss-Free Network; Självkörande Fordon; Datorseende; Djupinlärning; Maskininlärning; Multiuppgiftsinlärning; Överföringsinlärning; Uppgiftsrelationer; Uppgiftsdynamik; Python; Flerskalig Representationsinlärning; Fuss-Free Nätverk;

    Sammanfattning : Autonomous driving technology has the potential to revolutionize the way we think about transportation and its impact on society. Perceiving the environment is a key aspect of autonomous driving, which involves multiple computer vision tasks. LÄS MER