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Visar resultat 1 - 5 av 23 uppsatser som matchar ovanstående sökkriterier.

  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. A Deep Learning Approach To Vehicle Fault Detection Based On Vehicle Behavior

    Master-uppsats, Malmö universitet/Institutionen för datavetenskap och medieteknik (DVMT)

    Författare :Rafi Khaliqi; Cozma Iulian; [2023]
    Nyckelord :Deep learning; attention mechanism; vehicle fault detection; CNN; Bi-LSTM; Bi-GRU; Supervised classification;

    Sammanfattning : Vehicles and machinery play a crucial role in our daily lives, contributing to our transportationneeds and supporting various industries. As society strives for sustainability, the advancementof technology and efficient resource allocation become paramount. LÄS MER

  4. 3. Generation of a metrical grid informed by Deep Learning-based beat estimation in jazz-ensemble recordings

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

    Författare :Andres Alonso Toledo Carrera; [2023]
    Nyckelord :Beat tracking; Metrical grid; Jazz; Music Information Retrieval; Deep Learning; Temporal Convolutional Network; Beatuppskattning; Metriskt rutnät; Jazz; Music Informationshämting; Deep Learning; Temporal Convolutional Network;

    Sammanfattning : This work uses a Deep Learning architecture, specifically a state-of-the-art Temporal Convolutional Network, to track the beat and downbeat positions in jazz-ensemble recordings to derive their metrical grid. This network architecture has been used successfully for general beat tracking purposes. LÄS MER

  5. 4. A Comparative Analysis of Decision Tree Models in Identifying Landslide Susceptibility and Type Classification

    Kandidat-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Levi Jan Zuiverloon; [2023]
    Nyckelord :Landslides; landslide susceptibility mapping; Random Forest; Extreme Gradient Boosting; machine learning models; multiclass classification; binary classification; risk assessment; mitigation strategies; Italy; Aosta Valley; infrastructure vulnerability; supervised learning algorithms; Earth and Environmental Sciences;

    Sammanfattning : Landslides pose a significant risk to human life and infrastructure, especially in Italy, which has a high frequency of landslide occurrences. To mitigate these hazards, Landslide Susceptibility Mapping (LSM) is crucial for identifying risk areas and developing appropriate mitigation strategies. LÄS MER

  7. 5. EV - charger availability prediction based on machine learning

    Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Jainu Joseph; Jacob Sebastian; [2023]
    Nyckelord :;

    Sammanfattning : In response to the rapid growth of electric vehicles (EVs), our research focuses on the critical need for efficient management of charging infrastructure to facilitate the widespread adoption of EVs. Thisresearch leverages historical charging data as a foundation for predicting charging station availability. LÄS MER