Sökning: "inlärning genom bilder"
Visar resultat 1 - 5 av 52 uppsatser innehållade orden inlärning genom bilder.
1. Lärares användning av filmer och bilder för att stärka historieundervisningen
Uppsats för yrkesexamina på grundnivå, Malmö universitet/Fakulteten för lärande och samhälle (LS)Sammanfattning : Denna kunskapsöversikt syftar till att sammanställa forskning kring hur visuella hjälpmedel i form av filmer och bilder kan stötta inlärning och därmed stärka historieundervisningen. Historieämnet kan vara abstrakt för grundskoleelever, eftersom det är en del av den förflutna tiden som inte finns längre. LÄS MER
2. Self-learning for 3D segmentation of medical images from single and few-slice annotation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Training deep-learning networks to segment a particular region of interest (ROI) in 3D medical acquisitions (also called volumes) usually requires annotating a lot of data upstream because of the predominant fully supervised nature of the existing stateof-the-art models. To alleviate this annotation burden for medical experts and the associated cost, leveraging self-learning models, whose strength lies in their ability to be trained with unlabeled data, is a natural and straightforward approach. LÄS MER
3. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. LÄS MER
4. Unsupervised Domain Adaptation for Regressive Annotation : Using Domain-Adversarial Training on Eye Image Data for Pupil Detection
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Machine learning has seen a rapid progress the last couple of decades, with more and more powerful neural network models continuously being presented. These neural networks require large amounts of data to train them. LÄS MER
5. Unsupervised Domain Adaptation for 3D Object Detection Using Adversarial Adaptation : Learning Transferable LiDAR Features for a Delivery Robot
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : 3D object detection is the task of detecting the full 3D pose of objects relative to an autonomous platform. It is an important perception system that can be used to plan actions according to the behavior of other dynamic objects in an environment. LÄS MER