1 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
The Marine Debris Forward-Looking Sonar Datasets
Matias Valdenegro-Toro, Deepan Chakravarthi Padmanabhan, Deepak Singh +2
Sonar sensing is fundamental for underwater robotics, but limited by capabilities of AI systems, which need large training datasets. Public data in sonar modalities is lacking. Thi…
Self-supervised Learning for Sonar Image Classification
Alan Preciado-Grijalva, Bilal Wehbe, Miguel Bande Firvida +1
Self-supervised learning has proved to be a powerful approach to learn image representations without the need of large labeled datasets. For underwater robotics, it is of great int…
The Marine Debris Dataset for Forward-Looking Sonar Semantic Segmentation
Deepak Singh, Matias Valdenegro-Toro
Accurate detection and segmentation of marine debris is important for keeping the water bodies clean. This paper presents a novel dataset for marine debris segmentation collected u…
Pre-trained Models for Sonar Images
Matias Valdenegro-Toro, Alan Preciado-Grijalva, Bilal Wehbe
Machine learning and neural networks are now ubiquitous in sonar perception, but it lags behind the computer vision field due to the lack of data and pre-trained models specificall…
Forward-Looking Sonar Patch Matching: Modern CNNs, Ensembling, and Uncertainty
Arka Mallick, Paul Plöger, Matias Valdenegro-Toro
Application of underwater robots are on the rise, most of them are dependent on sonar for underwater vision, but the lack of strong perception capabilities limits them in this task…