Sökning: "Artificial Neural Networks"

Visar resultat 1 - 5 av 343 uppsatser innehållade orden Artificial Neural Networks.

  1. 1. Energy reconstruction with artificial neural networks on LDMX simulations

    Kandidat-uppsats, Lunds universitet/Partikelfysik; Lunds universitet/Fysiska institutionen

    Författare :Daniel Magdalinski; [2020]
    Nyckelord :Dark matter; LDMX; electromagnetic calorimeter; neural networks; convolutional neural networks; Physics and Astronomy;

    Sammanfattning : It is clear from evidence such as rotational curves and cosmic microwave background measurements that dark matter exists. The light dark matter experiment (LDMX) will search for dark matter in the sub-GeV range. It will do this using missing-momentum measurements of electrons interacting with a Tungsten target. LÄS MER

  2. 2. Implementation of a Deep Learning Inference Accelerator on the FPGA.

    Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknik

    Författare :Shenbagaraman Ramakrishnan; [2020]
    Nyckelord :Artificial Intelligence; Machine Learning; Deep Learning; Neural Networks; Deep Learning Accelerators; NVDLA; FPGA; Technology and Engineering;

    Sammanfattning : Today, Artificial Intelligence is one of the most important technologies, ubiquitous in our daily lives. Deep Neural Networks (DNN's) have come up as state of art for various machine intelligence applications such as object detection, image classification, face recognition and performs myriad of activities with exceptional prediction accuracy. LÄS MER

  3. 3. Topological recursive fitting trees : A framework for interpretable regression extending decision trees

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

    Författare :Alexandre Tadros; [2020]
    Nyckelord :;

    Sammanfattning : Many real-world machine learning applications need interpretation of an algorithm output. The simplicity of some of the most fundamental machine learning algorithms for regression, such as linear regression or decision trees, facilitates interpretation. However, they fall short when facing complex (e.g. LÄS MER

  4. 4. Deep Learning for Anomaly Detection in Microwave Links : Challenges and Impact on Weather Classification

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

    Författare :Olof Engström; [2020]
    Nyckelord :Anomaly Detection; Time Series; Forecasting; Weather Classification; Microwave Link; CNN; LSTM; Avvikelsedetektering; Tidsserier; Prognostisering; Väderklassificering; Mikrovågslänkar; faltningsnätverk; CNN; LSTM;

    Sammanfattning : Artificial intelligence is receiving a great deal of attention in various fields of science and engineering due to its promising applications. In today’s society, weather classification models with high accuracy are of utmost importance. LÄS MER

  5. 5. Prediction of Dose Probability Distributions Using Mixture Density Networks

    Master-uppsats, KTH/Matematisk statistik

    Författare :Viktor Nilsson; [2020]
    Nyckelord :Applied mathematics; machine learning; deep learning; mixture density network; dose planning; Tillämpad matematik; maskininlärning; djupinlärning; mixturdensitetsnätverk; dosplannerning;

    Sammanfattning : In recent years, machine learning has become utilized in external radiation therapy treatment planning. This involves automatic generation of treatment plans based on CT-scans and other spatial information such as the location of tumors and organs. LÄS MER