This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
Search
Skip to Search Results- 4Object Detection
- 2Computer Vision
- 2Deep Learning
- 2Remote Sensing
- 1Bark Beetle Attack Stage Classification
- 1Camera Calibration
-
Advancing Forest Health Monitoring: Harnessing the Power of Deep Learning Computer Vision for Remote Sensing Applications
DownloadFall 2023
Forests provide immense economic, ecological, and societal values, making forest health monitoring (FHM) a crucial task for guiding conservation and management of these essential ecosystems. Drones have seen increased popularity in this domain due to their ability to collect high-resolution,...
-
Spring 2024
Visual object detection predicts the categories of objects in an image and estimates bounding boxes that can wrap those objects accurately, playing a crucial role in many vision-based AI systems like autonomous cars, robotics, and smart monitoring. Although achieving significant progress, even...
-
Fall 2019
Object detection is an image processing technology to detection different classes of objects using computer vision, i.e. putting bounding boxes over objects from a camera video feed. A landmark detection method was the Viola-Jones Algorithm introduced in 2001. The object classifier in this...
-
Spring 2024
Pattern recognition aims to differentiate patterns and regularities across diverse data types. Pattern recognition can identify unfamiliar objects, localize objects from various perspectives or resolutions, and infer patterns even when they are partially occluded. The ubiquity of sensors in...