Sökning: "real-time object localization"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden real-time object localization.

1. 1. Real-time Human Detection using Convolutional Neural Networks with FMCW RADAR RGB data

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Anna Phan; Rogelio Medina; [2022]
   Nyckelord :Human Detection; Machine Learning; Convolutional Neural Networks; YOLO; FMCW Radar; Human Detection Evaluation; Människodetektering; Maskininlärning; Neurala faltningsnät; Djupa faltningsnät; YOLO; FMCW Radar; Utvärdering;

   Sammanfattning : Machine learning has been employed in the automotive industry together with cameras to detect objects in surround sensing technology. You Only Look Once is a state-of-the-art object detection algorithm especially suitable for real-time applications due to its speed and relatively high accuracy compared to competing methods. LÄS MER

3. 2. Guardrail detection for landmark-based localization

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

   Författare :Nils Gumaelius; [2022]
   Nyckelord :computer vision; LiDAR; object detection; localization; landmark-based localization; guardrail detection; dbscan; autonomous driving;

   Sammanfattning : A requirement for safe autonomous driving is to have an accurate global localization of the ego vehicle. Methods based on Global Navigation Satellite System (GNSS) are the most common but are not precise enough in areas without good satellite signals. Instead, methods likelandmark-based localization (LBL) can be used. LÄS MER

4. 3. The V-SLAM Hurdler : A Faster V-SLAM System using Online Semantic Dynamic-and-Hardness-aware Approximation

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

   Författare :Liu Mingxuan; [2022]
   Nyckelord :Approximate Computing; Deep Learning; Dynamic Environments; Object Detection; Online Controller; Semantic SLAM; Ungefärlig Beräkning; Djup Lärning; Dynamiska miljöer; Objektdetektion; Online Kontroller; Semantisk SLAM;

   Sammanfattning : Visual Simultaneous Localization And Mapping (V-SLAM) and object detection algorithms are two critical prerequisites for modern XR applications. V-SLAM allows XR devices to geometrically map the environment and localize itself within the environment, simultaneously. LÄS MER

5. 4. Relative pose estimation of a plane on an airfield with automotive-class solid-state LiDAR sensors : Enhancing vehicular localization with point cloud registration

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

   Författare :Marco Casagrande; [2021]
   Nyckelord :Point Cloud Registration; Iterative Closest Point; Relative Localization; Automotive Class LiDAR; Point Cloud Registrering; Iterative Closest Point; Relativ Lokalisering; LiDAR;

   Sammanfattning : Point cloud registration is a technique to align two sets of points with manifold applications across a range of industries. However, due to a lack of adequate sensing technology, this technique has seldom found applications in the automotive sector up to now. LÄS MER

7. 5. Real-time localization of balls and hands in videos of juggling using a convolutional neural network

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :Rasmus Åkerlund; [2019]
   Nyckelord :convolutional neural network; real-time object localization; large video dataset; juggling;

   Sammanfattning : Juggling can be both a recreational activity that provides a wide variety of challenges to participants and an art form that can be performed on stage. Non-learning-based computer vision techniques, depth sensors, and accelerometers have been used in the past to augment these activities. LÄS MER