Essays about: "semantic generation"

Showing result 1 - 5 of 32 essays containing the words semantic generation.

  1. 1. Replacing Objects in Point Cloud stream with Real-time Meshes using Semantic Segmentation

    University essay from Blekinge Tekniska Högskola

    Author : Abhinav Chitta; [2024]
    Keywords : ;

    Abstract : Background: The evolving landscape of 3D data processing, particularly pointcloud manipulation, is pivotal in numerous applications ranging from architecturaldesign to spatial analysis. Traditional methods, primarily mesh generation from point clouds, face challenges in adapting to complex real-world scenarios. READ MORE

  3. 2. Generating Wikipedia Articles with Grammatical Framework : A Case Study

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Keivan Matinzadeh; [2023]
    Keywords : Grammatical Framework; Computational Linguistics; Natural Language Generation; Computer Science; Grammatical Framework; Beräkningslingvistik; Textgenerering; Datavetenskap;

    Abstract : Natural language generation is a method used to produce understandable texts in human languages from data [1]. Grammatical Framework is a grammar formalism and a functional programming language using a nonstatistical approach to build natural language applications. READ MORE

  4. 3. Using a Deep Generative Model to Generate and Manipulate 3D Object Representation

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Yu Hu; [2023]
    Keywords : Neural networks; point cloud; 3D shape generation; 3D shape manipulation; classification; Neurala nätverk; punktmoln; generering av 3D-former; manipulation av 3Dformer; klassificering;

    Abstract : The increasing importance of 3D data in various domains, such as computer vision, robotics, medical analysis, augmented reality, and virtual reality, has gained giant research interest in generating 3D data using deep generative models. The challenging problem is how to build generative models to synthesize diverse and realistic 3D objects representations, while having controllability for manipulating the shape attributes of 3D objects. READ MORE

  5. 4. Scenario Generation For Vehicles Using Deep Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Jay Patel; [2022]
    Keywords : Scenario generation; Mixture Density Network; Gaussian Mixture Model; Autonomous driving; Semantic Graph Network; Scenariogenerering; Mixture Density Network; Gaussian Mixture Model; Autonom körning; Semantic Graph Network;

    Abstract : In autonomous driving, scenario generation can play a critical role when it comes to the verification of the autonomous driving software. Since uncertainty is a major component in driving, there cannot be just one right answer to a prediction for the trajectory or the behaviour, and it becomes important to account for and model that uncertainty. READ MORE

  6. 5. Creating a semantic segmentationmachine learning model for sea icedetection on radar images to study theThwaites region

    University essay from Luleå tekniska universitet/Rymdteknik

    Author : Carmen Fuentes Soria; [2022]
    Keywords : Synthetic Aperture Radar SAR ; Machine Learning ML ; Semantic segmentation; Convolutional Neural Networks CNN ; Thwaites Glacier;

    Abstract : This thesis presents a deep learning tool able to identify ice in radar images fromthe sea-ice environment of the Twhaites glacier outlet. The project is motivatedby the threatening situation of the Thwaites glacier that has been increasingits mass loss rate during the last decade. READ MORE