Andrew B. Barron — accepted AI-conference papers

2022

EchoVPR: Echo State Networks for Visual Place Recognition

Anil Özdemir, Mark Scerri, Andrew B. Barron, Andrew Philippides, Michael Mangan, Eleni Vasilaki +1

RA-L 2022

Recognising previously visited locations is an important, but unsolved, task in autonomous navigation. Current visual place recognition (VPR) benchmarks typically challenge models to recover the position of a query image (or images) from sequential datasets that include both spatial and temporal com

Cited by 10 Source ↗code ↗Scholar ↗

2020

A Hybrid Compact Neural Architecture for Visual Place Recognition

Marvin Chancán, Luis Hernandez-Nunez, Ajay Narendra, Andrew B. Barron, Michael Milford

RA-L 2020

State-of-the-art algorithms for visual place recognition, and related visual navigation systems, can be broadly split into two categories: computer-science-oriented models including deep learning or image retrieval-based techniques with minimal biological plausibility, and neuroscience-oriented dyna

Cited by 59 Source ↗Scholar ↗