Sökning: "Bridge classification"
Visar resultat 1 - 5 av 20 uppsatser innehållade orden Bridge classification.
1. Uncertainty Quantification in Deep Learning for Breast Cancer Classification in Point-of-Care Ultrasound Imaging
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : Breast cancer is the most common type of cancer worldwide with an estimate of 2.3 million new cases in 2020, and the number one cause of cancer-related deaths in women. LÄS MER
2. Performance metrics and velocity influence for point cloud registration in autonomous vehicles
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : Autonomous vehicles are currently under study and one of the critical parts is the localization of the vehicle in the environment. Different localization methods have been studied over the years, such as the GPS sensor, commonly fused with other sensors such as the IMU. LÄS MER
3. Meta-Pseudo Labelled Multi-View 3D Shape Recognition
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The field of computer vision has long pursued the challenge of understanding the three-dimensional world. This endeavour is further fuelled by the increasing demand for technologies that rely on accurate perception of the 3D environment such as autonomous driving and augmented reality. LÄS MER
4. Attribute Embedding for Variational Auto-Encoders : Regularization derived from triplet loss
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Techniques for imposing a structure on the latent space of neural networks have seen much development in recent years. Clustering techniques used for classification have been used to great success, and with this work we hope to bridge the gap between contrastive losses and Generative models. LÄS MER
5. CLASSIFICATION OF BRIDGES IN LASER POINT CLOUDS USING MACHINE LEARNING
Master-uppsats, Mälardalens högskola/Akademin för innovation, design och teknikSammanfattning : In this work, machine learning was being used for bridge detection in point clouds. To estimate the performance, it was compared to an existing algorithm based on traditional methods for point classification. The purpose of this work was to use machine learning for bridge classification in point clouds. LÄS MER