Giovanni G. De Giacomo — accepted AI-conference papers

2022

Cross-View and Cross-Domain Underwater Localization Based on Optical Aerial and Acoustic Underwater Images

Matheus Machado dos Santos, Giovanni G. De Giacomo, Paulo L. J. Drews-Jr, Silvia S. C. Botelho

RA-L 2022

Cross-view image matches have been widely explored on terrestrial image localization using aerial images from drones or satellites. This study expands the cross-view image match idea and proposes a cross-domain and cross-view localization framework. The method identifies the correlation between colo

Cited by 19 Source ↗Scholar ↗

2020

Matching Color Aerial Images and Underwater Sonar Images Using Deep Learning for Underwater Localization

Matheus Machado dos Santos, Giovanni G. De Giacomo, Paulo L. J. Drews-Jr, Silvia S. C. Botelho

RA-L 2020

Underwater localization is a challenging task due to the lack of a Global Positioning System (GPS). However, the capability to match georeferenced aerial images and acoustic data can help with this task. Autonomous hybrid aerial and underwater vehicles also demand a new localization method capable o

Cited by 41 Source ↗Scholar ↗