Sökning: "Deep Monte-Carlo"

Visar resultat 1 - 5 av 50 uppsatser innehållade orden Deep Monte-Carlo.

  1. 1. Evaluating image analysis techniques for ultrasound optical tomography in breast tissue

    Master-uppsats, Lunds universitet/Avdelningen för Biomedicinsk teknik

    Författare :Henrik von Friesendorff; [2023]
    Nyckelord :ultrasound optical tomography; Monte Carlo light simulation; image reconstruction; Technology and Engineering;

    Sammanfattning : Breast cancer is the most commonly diagnosed cancer in the world today and early detection is crucial to minimize the mortality. ”Ultrasound optical tomography” (UOT) is a method under development for deep tissue imaging. LÄS MER

  3. 2. Multiclass Brain Tumour Tissue Classification on Histopathology Images Using Vision Transformers

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Christoforos Spyretos; [2023]
    Nyckelord :medical imaging; deep learning; classification; CNN; Vision Transformer; glioblastoma; GBM; IvyGAP; brain tumour; histopathology; digital pathology; histology;

    Sammanfattning : Histopathology refers to inspecting and analysing tissue samples under a microscope to identify and examine signs of diseases. The manual investigation procedure of histology slides by pathologists is time-consuming and susceptible to misconceptions. LÄS MER

  4. 3. Modeling and Simulation for Forward Arming and Refueling Points : Enhancing efficiency and Decision- making in Military Operations

    Master-uppsats, Försvarshögskolan

    Författare :Philip Muurmans; [2023]
    Nyckelord :FARP; military operation; military logistics; military capability; Modeling and Simulation; Monte Carlo simulation; discrete event simulation; IS framework;

    Sammanfattning : This master’s thesis explores the application of Modeling and Simulation (M&S) techniques in military operations involving Forward Arming and Refueling Points (FARP). FARPs play a crucial role in supporting aircraft operations by facilitating deep penetration into enemy territory and ensuring sustained presence in the Area of Operation (AOO). LÄS MER

  5. 4. Clinical Assessment of Deep Learning-Based Uncertainty Maps in Lung Cancer Segmentation

    Master-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

    Författare :Federica Carmen Maruccio; [2023]
    Nyckelord :3D U-Net; Contouring; Clinical validation; Deep learning; Lung cancer; Monte Carlo dropout; Probability map; Reliability diagram; Segmentation; Uncertainty map;

    Sammanfattning : Prior to radiation therapy planning, tumours and organs at risk need to be delineated. In recent years, deep learning models have opened the possibility of automating the contouring process, speeding up the procedures and helping clinicians. LÄS MER

  7. 5. Real-time uncertainty estimation for deep learning

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

    Författare :Árni Dagur Guðmundsson; [2023]
    Nyckelord :Machine Learning; Deep Learning; Uncertainty Estimation; Evidential Deep Learning; Computer Vision; Maskininlärning; Djupinlärning; Osäkerhetsuppskattning; Evidential Deep Learning; Datorseende; Vélnám; Djúptauganet; Óvissumat; Evidential Deep Learning; Tölvusjón;

    Sammanfattning : Modern deep neural networks do not produce well calibrated estimates of their own uncertainty, unless specific uncertainty estimation techniques are applied. Common uncertainty estimation techniques such as Deep Ensembles and Monte Carlo Dropout necessitate multiple forward pass evaluations for each input sample, making them too slow for real-time use. LÄS MER