Sökning: "Small Object Detection"

Visar resultat 1 - 5 av 78 uppsatser innehållade orden Small Object Detection.

  1. 1. 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

  3. 2. IDENTIFICATION OF ENVIRONMENTALLY RELEVANT BENTHIC FORAMINIFERA FROM THE SKAGERRAK FJORDS BY DEEP LEARNING IMAGE MODELING

    Master-uppsats, Göteborgs universitet / Institutionen för biologi och miljövetenskap

    Författare :Marko Plavetic; [2023-06-26]
    Nyckelord :benthic foraminifera; deep learning; environmental monitoring; YOLOv7;

    Sammanfattning : Over the several past decades, there has been increasing interest in using foraminifera as environmental indicators for coastal marine environments. As compared to macrofauna, which are currently used in environmental studies, foraminifera offer several distinct advantages as bioindicators, including short generation times, a high number of individuals per small sample volume, hard and durable tests with high preservation potential, and low cost of sample extraction. LÄS MER

  4. 3. Optimization of Speed vs. Accuracy Trade-off in State-of-the-Art Object Detectors for Traffic Light Detection

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

    Författare :Vikash Lal Dodani; [2023]
    Nyckelord :Machine Learning; Computer Vision; Traffic Lights Detection; Self-Driving Cars; BOSCH; BSTLD; LISA;

    Sammanfattning : Traffic lights detection systems are an important area of research, aimed towards improving the accuracy and response time of self-driving vehicles when faced with traffic signals. This project attempted to find a solution for the speed-accuracy trade-off faced by traffic light detection systems. 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. Performance analysis of the communication system of a drone prototype used for maintenance and cleaning

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Abhinav Siddharth Mekam; [2023]
    Nyckelord :Drone; Pixhawk 6C; Raspberry pi; MAVlink protocol; Haarcascade classifier; OpenCV.;

    Sammanfattning : Drones in today’s life are used in many sectors to automate various tasks. Delivering small items, capturing live events, and surveying dangerous areas are a few incredible operations of drones in today’s society. It can perform many tasks in human-restricted areas with less service time and cost. LÄS MER