1 code implementation • 11 Oct 2021 • Anil Ozdemir, Mark Scerri, Andrew B. Barron, Andrew Philippides, Michael Mangan, Eleni Vasilaki, Luca Manneschi
We report that the addition of ESNs to pre-processed convolutional neural networks led to a dramatic boost in performance in comparison to non-recurrent networks in five out of six standard benchmarks (GardensPoint, SPEDTest, ESSEX3IN1, Oxford RobotCar, and Nordland), demonstrating that ESNs are able to capture the temporal structure inherent in VPR problems.
1 code implementation • 15 Oct 2019 • Marvin Chancán, Luis Hernandez-Nunez, Ajay Narendra, Andrew B. Barron, Michael Milford
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 dynamical networks that model temporal properties underlying spatial navigation in the brain.