Sökning: "Automatic Inspection"
Visar resultat 1 - 5 av 44 uppsatser innehållade orden Automatic Inspection.
1. Sim2Real: Generating synthetic images from industry CAD models with domain randomization
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Deep learning methods for computer vision applications require massive visual data for model training. Although it is possible to utilize public datasets such as ImageNet, MS COCO, and CIFAR-100, it becomes problematic when there is a need for more task-specific data when new training data collection typically is needed. LÄS MER
2. Locating power lines in satellite images with semantic segmentation
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : The inspection of power lines is an important process to maintain a stable electrical infrastructure. Simultaneously it is very time consuming task considering there are 164 000 km of power lines in Sweden alone. A cheaper and more sustainable approach is an automatic inspection with drones. LÄS MER
3. A Deep Learning Based Approach to Object Recognition from LiDAR Data Along Swedish Railroads
Master-uppsats, KTH/Fastigheter och byggandeSammanfattning : Malfunction in the overhead contact line system is a common cause of disturbances in the train traffic in Sweden. Due to the preventive methods being inefficient, the Swedish Transport Administration has stated the need to develop the railroad maintenance services and has identified Artificial Intelligence (AI) as an important tool for this undertaking. LÄS MER
4. An Industrial Application of Semi-supervised techniques for automatic surface inspection of stainless steel. : Are pseudo-labeling and consistency regularization effective in a real industrial context?
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Recent developments in the field of Semi-Supervised Learning are working to avoid the bottleneck of data labeling. This can be achieved by leveraging unlabeled data to limit the amount of labeled data needed for training deep learning models. LÄS MER
5. Towards Condition-Based Maintenance of Catenary wires using computer vision : Deep Learning applications on eMaintenance & Industrial AI for railway industry
Master-uppsats, Luleå tekniska universitet/Institutionen för samhällsbyggnad och naturresurserSammanfattning : Railways are a main element of a sustainable transport policy in several countries as they are considered a safe, efficient and green mode of transportation. Owing to these advantages, there is a cumulative request for the railway industry to increase the performance, the capacity and the availability in addition to safely transport goods and people at higher speeds. LÄS MER