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Visar resultat 1 - 5 av 13 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Collaborative Exploration with Intermittent Communication : Inferring map information from exploration graphs

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

    Författare :Viktor Åkerblom Jonsson; [2023]
    Nyckelord :;

    Sammanfattning : Autonomous robots have a substantial presence in today’s society. A presence which increases with each passing year, as more and more problems may be handled by robots. As challenges in the field of Robotics are conquered, the field expands and new challenges appear. LÄS MER

  3. 2. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases

    Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Oskar Nilsson; Benjamin Lilje; [2023]
    Nyckelord :Machine Learning; Deep Learning; Reject Inference; GNN; GCN; Graph Neural Networks; RNN; Recursive Neural Network; LSTM; Semi-Supervised Learning; Encoding; Decoding; Feature Elimination;

    Sammanfattning : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. LÄS MER

  4. 3. A graph database implementation of an event recommender system

    M1-uppsats,

    Författare :Alexander Olsson; [2022]
    Nyckelord :Event; Recommender system; Neo4j; Graph database;

    Sammanfattning : The internet is larger than ever and so is the amount of information on the internet.The average user on the internet has next to endless possibilities and choices whichcan cause information overload. Companies have therefore developed systems toguide their users to find the right product or object in the form of recommendersystems. LÄS MER

  5. 4. Multimodal Machine Learning in Human Motion Analysis

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

    Författare :Jia Fu; [2022]
    Nyckelord :Multimodal machine learning; Modal fusion; Human motion classification; Multimodal maskininlärning; Modal fusion; Mänsklig rörelseklassificering;

    Sammanfattning : Currently, most long-term human motion classification and prediction tasks are driven by spatio-temporal data of the human trunk. In addition, data with multiple modalities can change idiosyncratically with human motion, such as electromyography (EMG) of specific muscles and respiratory rhythm. LÄS MER

  7. 5. Comparison of state-of-the-art Temporal Interaction Network methods in different settings : Novel models to predict temporal behavior

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

    Författare :Indre Tauroseviciute; [2021]
    Nyckelord :Recommendation systems; Neural Collaborative Filtering; RNN; Backpropagation; Comparative analysis;

    Sammanfattning : Recommendation systems become more and more necessary due to the growing supply chain. Therefore, scientists are developing models that can serve different recommendation needs faster than before, and it is getting more complicated to choose the model for a specific case. LÄS MER