Sökning: "Semi-automatic data labeling"

Hittade 4 uppsatser innehållade orden Semi-automatic data labeling.

1. 1. Using active learning for semi-automatically labeling a dataset of fisheye distorted images for object detection

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Olof Bourghardt; [2022]
   Nyckelord :Machine learning; Object detection; Computer vision; Semi-automatic data labeling; Fisheye images;

   Sammanfattning : Self-driving vehicles has become a hot topic in today's industry during the past years and companies all around the globe are attempting to solve the complex task of developing vehicles that can safely navigate roads and traffic without the assistance of a driver.  As deep learning and computer vision becomes more streamlined and with the possibility of using fisheye cameras as a cheap alternative to external sensors some companies have begun researching the possibility for assisted driving on vehicles such as electrical scooters to prevent injuries and accidents by detecting dangerous situations as well as promoting a sustainable infrastructure. LÄS MER

3. 2. Collision Avoidance for Complex and Dynamic Obstacles : A study for warehouse safety

   Master-uppsats, Linköpings universitet/Reglerteknik

   Författare :Sandra Ljungberg; Ester Brandås; [2022]
   Nyckelord :Object Detection; Object Tracking; Obstacle Avoidance; Collision Avoidance; Automated Guided Vehicle;

   Sammanfattning : Today a group of automated guided vehicles at Toyota Material Handling Manufacturing Sweden detect and avoid objects primarily by using 2D-LiDAR, with shortcomings being the limitation of only scanning the area in a 2D plane and missing objects close to the ground. Several dynamic obstacles exist in the environment of the vehicles. LÄS MER

4. 3. LiDAR Pedestrian Detector and Semi-Automatic Annotation Tool for Labeling of 3D Data

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Roy Andersson; Erik Andersson; [2019]
   Nyckelord :LiDAR; Machine Learning; Pedestrian Detection; Annotation; DBSCAN; SVM; Technology and Engineering;

   Sammanfattning : The goal of this Master's Thesis is to successfully detect and classify humans in a LiDAR data stream. The focus of the Thesis is on the detection and classification, not on the LiDAR technology. To classify humans machine learning was used and to train the machine learning model we collected our own data and annotated it. LÄS MER

5. 4. Towards unification of organ labeling in radiation therapy using a machine learning approach based on 3D geometries

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

   Författare :Giorgio Ruffa; [2019]
   Nyckelord :;

   Sammanfattning : In radiation therapy, it is important to control the radiation dose absorbed by Organs at Risk (OARs). The OARs are represented as 3D volumes delineated by medical experts, typically using computed tomography images of the patient. LÄS MER