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Visar resultat 1 - 5 av 140 uppsatser som matchar ovanstående sökkriterier.

  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. Real time Optical  Character Recognition  in  steel  bars  using YOLOV5

    Master-uppsats, Blekinge Tekniska Högskola

    Författare :Monica Gattupalli; [2023]
    Nyckelord :Deep learning; Object detection; Tesseract OCR; YOLOV5; YOLOV5- obb;

    Sammanfattning : Background.Identifying the quality of the products in the manufacturing industry is a challenging task. Manufacturers use needles to print unique numbers on the products to differentiate between good and bad quality products. However, identi- fying these needle printed characters can be difficult. LÄS MER

  4. 3. Smart Tracking for Edge-assisted Object Detection : Deep Reinforcement Learning for Multi-objective Optimization of Tracking-based Detection Process

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

    Författare :Shihang Zhou; [2023]
    Nyckelord :Tracking-By-Detection; Deep Reinforcement Learning; Multi-Objective Optimization; Spårning genom detektion; Djup förstärkningsinlärning; Multiobjektiv optimering;

    Sammanfattning : Detecting generic objects is one important sensing task for applications that need to understand the environment, for example eXtended Reality (XR), drone navigation etc. However, Object Detection algorithms are particularly computationally heavy for real-time video analysis on resource-constrained mobile devices. LÄS MER

  5. 4. Automated annotation scheme for extending bounding box representation to detect ship locations.

    Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

    Författare :Oksana Havryliuk; [2023]
    Nyckelord :;

    Sammanfattning : Bounding boxes often provide limited information about the shape and location of an object on an image. Their limitations lie in their reduced ability to correctly represent objects that have complex shapes or are located at an angle. LÄS MER

  7. 5. Data Augmentations for Improving Vision-Based Damage Detection : in Land Transport Infrastructure

    Master-uppsats, KTH/Lantmäteri – fastighetsvetenskap och geodesi

    Författare :Punnawat Siripatthiti; [2023]
    Nyckelord :Computer Vision; Data Augmentation; Object Detection; Crack Detection; Road Damage Detection; Sleeper Defect Detection; datorseende; dataökning; objektdetektering; sprickdetektering; vägbeläggning; järnvägsslipers;

    Sammanfattning : Crack, a typical term most people know, is a common form of distress or damage in road pavements and railway sleepers. It poses significant challenges to their structural integrity, safety, and longevity. Over the years, researchers have developed various data-driven technologies for image-based crack detection in road and sleeper applications. LÄS MER