Sökning: "computer applications"

Visar resultat 1 - 5 av 858 uppsatser innehållade orden computer applications.

  1. 1. Automatic Semantic Segmentation of Indoor Datasets

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Sai Swaroop Rachakonda; [2024]
    Nyckelord :Semantic Segmentation; Annotation; SLAM; Indoor datasets; YOLO V8; DETIC; Segment Anything Model.;

    Sammanfattning : Background: In recent years, computer vision has undergone significant advancements, revolutionizing fields such as robotics, augmented reality, and autonomoussystems. Key to this transformation is Simultaneous Localization and Mapping(SLAM), a fundamental technology that allows machines to navigate and interactintelligently with their surroundings. LÄS MER

  3. 2. 3D/VR - Data flow visualization

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Sudheer Sujay; [2024]
    Nyckelord :;

    Sammanfattning : This thesis delves into the realm of Virtual Reality (VR) to explore its potential for visualizing data flows in intricate systems. Focused on the transition from conventional 2D representations to immersive 3D experiences, the study employs Unity and Oculus Quest 2 for prototyping. LÄS MER

  4. 3. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks

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

    Författare :Xinchen Wang; [2024]
    Nyckelord :Deep Learning; Semantic segmentation; Network optimization; Network pruning; Torch Pruning; YOLOv8; Network Depth; Djup lärning; Semantisk segmentering; Nätverksoptimering; Nätverksbeskärning; Fackelbeskärning; YOLOv8; Nätverksdjup;

    Sammanfattning : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. LÄS MER

  5. 4. Movement Estimation with SLAM through Multimodal Sensor Fusion

    Master-uppsats, Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakulteten

    Författare :Jimmy Cedervall Lamin; [2024]
    Nyckelord :slam; discrete-slam; continuous-slam; synchronous; asynchronous; computer vision; BRISK; opencv; ceres; visual; inertial; sensor fusion; multimodal; Simultaneous Localization and Mapping; time offset; pose estimation; quaternions; movement estimation;

    Sammanfattning : In the field of robotics and self-navigation, Simultaneous Localization and Mapping (SLAM) is a technique crucial for estimating poses while concurrently creating a map of the environment. Robotics applications often rely on various sensors for pose estimation, including cameras, inertial measurement units (IMUs), and more. LÄS MER

  7. 5. Incremental Re-tokenization in BPE-trained SentencePiece Models

    Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Simon Hellsten; [2024]
    Nyckelord :BPE; Byte Pair Encoding; SentencePiece; NLP; Natural Language Processing; Tokenization; Re-tokenization;

    Sammanfattning : This bachelor's thesis in Computer Science explores the efficiency of an incremental re-tokenization algorithm in the context of BPE-trained SentencePiece models used in natural language processing. The thesis begins by underscoring the critical role of tokenization in NLP, particularly highlighting the complexities introduced by modifications in tokenized text. LÄS MER