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Visar resultat 1 - 5 av 66 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Virtual H&E Staining Using PLS Microscopy and Neural Networks

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Sally Vizins; Hanna Råhnängen; [2024]
    Nyckelord :Deep learning; Virtual staining; Skin tissue; Hematoxylin Eosin; H E; Pathology; Carcinoma; Point light source illumination; Neural Networks; GANs; Generative adversarial networks; CNNs; Convolutional neural networks; Relativistic generative adversarial network; Unet; Digital microscopy; Attention-Unet; Dense-Unet; Mathematics and Statistics;

    Sammanfattning : Histopathological examination, crucial in diagnosing diseases such as cancer, traditionally relies on time- and resource-consuming, poorly standardized chemical staining for tissue visualization. This thesis presents a novel digital alternative using generative neural networks and a point light source (PLS) microscope to transform unstained skin tissue images into their stained counterparts. LÄS MER

  3. 2. Evaluating and optimizing Transformer models for predicting chemical reactions

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

    Författare :Siva Manohar Koki; Supriya Kancharla; [2023-10-23]
    Nyckelord :Chemformer; transformer; evaluation; explainable AI; fine-tuning; machine learning;

    Sammanfattning : In this thesis, we assess the effectiveness of a transformer model specifically trained to predict chemical reactions. The model, named Chemformer, is a sequence-tosequence model that uses the transformer’s encoder and decoder stacks. LÄS MER

  4. 3. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis

    Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Laura Galera Alfaro; [2023]
    Nyckelord :Explainable Artificial Intelligence; Learning To Rank; Local ModelAgnostic Interpretability; Ranking Generalized Additive Models;

    Sammanfattning : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. LÄS MER

  5. 4. Exploring Advanced Clustering Techniques for Business Descriptions : A Comparative Study and Analysis of DBSCAN, K-Means, and Hierarchical Clustering

    Uppsats för yrkesexamina på avancerad nivå, Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)

    Författare :Wisam Orabi Alkhen; [2023]
    Nyckelord :Machine learning; Business descriptions; Search scope reduction; Relevant business terminology; Data analysis.;

    Sammanfattning : In this study, we introduce several approaches to analyze large volumes of business descriptions by applying machine learning clustering and classification algorithms. The goal is to efficiently classify these descriptions, reducing the search scope and allowing for better business insights and decision-making processes. LÄS MER

  7. 5. Episodic memory and scene perception, an eye-tracking experiment with induced cognitive load.

    Master-uppsats, Lunds universitet/Institutionen för psykologi

    Författare :Lejla Fazlic; [2023]
    Nyckelord :Keywords: Episodic memory; Scanpath Similarity; cognitive load; scene perception; eye-tracking.; Social Sciences;

    Sammanfattning : This study investigates if cognitively induced load via the Sternberg Task influences episodic memory measured through eye metrics data. An eye-tracking experiment was conducted with 34 participants to research if memory will decline when cognitive load increases. The method was a block design, controlled experiment. LÄS MER