Essays about: "YOLO V8"

Found 4 essays containing the words YOLO V8.

  1. 1. Automatic Semantic Segmentation of Indoor Datasets

    University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

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

    Abstract : 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. READ MORE

  2. 2. A Novel Approach for Rice Plant Disease Detection, classification and localization using Deep Learning Techniques

    University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Author : Surya S V A S Sudheer Vadrevu; [2023]
    Keywords : Machine Learning; Image Processing; Disease Diagnosis; robustnessand reliability; SegFormer; Mask RCNN; YOLO v8;

    Abstract : Background. This Thesis addresses the critical issue of disease management in ricecrops, a key factor in ensuring both food security and the livelihoods of farmers. Objectives. READ MORE

  3. 3. Real Time Vehicle Detection for Intelligent Transportation Systems

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Elda Shurdhaj; Ulehla Christián; [2023]
    Keywords : Unmanned aerial vehicles UAVs ; vehicle detection; CNN architecture; snow cover; NVD; Yolov5s; Yolov8s; Faster R-CNN; real-time processing; edge devices;

    Abstract : This thesis aims to analyze how object detectors perform under winter weather conditions, specifically in areas with varying degrees of snow cover. The investigation will evaluate the effectiveness of commonly used object detection methods in identifying vehicles in snowy environments, including YOLO v8, Yolo v5, and Faster R-CNN. READ MORE

  4. 4. ERROR DETECTION IN PRODUCTION LINES VIA DEPENDABLE ARCHITECTURES IN CONVOLUTIONAL NEURAL NETWORKS

    University essay from Mälardalens universitet/Akademin för innovation, design och teknik

    Author : Erik Olsson; [2023]
    Keywords : Neural Networks; Production lines; Faster R-CNN; YOLO V8;

    Abstract : The need for products has increased during the last few years, this high demand needs to bemet with higher means of production. The use of neural networks can be the key to increasedproduction without having to compromise product quality or human workers well being. READ MORE