Browsing by Author "Warakagoda, Narada Dilp"
Now showing items 1-7 of 7
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Challenges of Automated Change Detection in Repeat-pass Synthetic Aperture Sonar Imagery
Midtgaard, Øivind; Sæbø, Torstein Olsmo; Warakagoda, Narada Dilp (2023)Change detection extracts regions of interest as temporal differences by imaging a scene before and after changes may have occurred. We denote the initial image as the reference and the more recent as the current image. ... -
Challenges of Labelling Unknown Seabed Munition Dumpsites from Acoustic and Optical Surveys: A Case Study at Skagerrak
Bryan, Oscar; Hansen, Roy Edgar; Haines, Tom S. F.; Warakagoda, Narada Dilp; Hunter, Alan Joseph (2022-05-31)The disposal of unexploded ordnance (UXOs) at sea is a global problem. The mapping and remediation of historic UXOs can be assisted by autonomous underwater vehicles (AUVs) carrying sensor payloads such as synthetic aperture ... -
Generative Adversarial Immitation Learning for Steering an Unmanned Surface Vehicle
Vedeler, Alexandra Skau; Warakagoda, Narada Dilp (2020-02)The task of obstacle avoidance using maritime vessels, such as Unmanned Surface Vehicles (USV), has traditionally been solved using specialized modules that are designed and optimized separately. However, this approach ... -
Multi-phase performance evaluation for modern minehunting systems
Midtgaard, Øivind; Warakagoda, Narada Dilp; Davies, Gary; Connors, Warren A.; Geilhufe, Marc (2019-05-10)Many NATO navies are in the process of replacing their dedicated minehunting vessels with systems of heterogeneous, unmanned modules. While traditional ship-based assets prosecute sonar contacts in sequence through to ... -
A Study on the Effect of Commonly Used Data Augmentation Techniques on Sonar Image Artifact Detection Using Deep Neural Networks
Orescanin, Marco; Harrington, Brian; Olson, Derek R.; Geilhufe, Marc; Hansen, Roy Edgar; Warakagoda, Narada Dilp (2023-10-20)This paper presents an empirical study that evaluates the impact of different types of augmentations on the performance of Deep Learning (DL) models for detecting imaging artifacts in Synthetic Aperture Sonar (SAS) imagery. ... -
Towards Using Reinforcement Learning for Autonomous Docking of Unmanned Surface Vehicles
Holen, Martin; Ruud, Else-Line Malene; Warakagoda, Narada Dilp; Granmo, Ole-Christoffer; Engelstad, Paal E.; Knausgård, Kristian Muri (2022-06-10)Providing full autonomy to Unmanned Surface Vehicles (USV) is a challenging goal to achieve. Autonomous docking is a subtask that is particularly difficult. The vessel has to distinguish between obstacles and the dock, and ... -
Uncertainty quantification with deep learning through variational inference with applications to synthetic aperture sonar
Orescanin, Marco; Harrington, Brian; Olson, Derek R.; Geilhufe, Marc; Hansen, Roy Edgar; Warakagoda, Narada Dilp (2023)Deep learning (DL) has gained popularity in applications and research within the active sonar community both in academic and commercial settings due to the ability of such models to learn complex non-linear relationships ...