Bruno Arcanjo — accepted AI-conference papers

2024

Aggregating Multiple Bio-Inspired Image Region Classifiers for Effective and Lightweight Visual Place Recognition

Bruno Arcanjo, Bruno Ferrarini, Maria Fasli, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan

RA-L 2024

Visual place recognition (VPR) enables autonomous systems to localize themselves within an environment using image information. While VPR techniques built upon a Convolutional Neural Network (CNN) backbone dominate state-of-the-art VPR performance, their high computational requirements make them uns

Cited by 1 Source ↗Scholar ↗

2022

An Efficient and Scalable Collection of Fly-Inspired Voting Units for Visual Place Recognition in Changing Environments

Bruno Arcanjo, Bruno Ferrarini, Michael Milford, Klaus D. McDonald-Maier, Shoaib Ehsan

RA-L 2022

State-of-the-art visual place recognition performance is currently being achieved utilizing deep learning based approaches. Despite the recent efforts in designing lightweight convolutional neural network based models, these can still be too expensive for the most hardware restricted robot applicati

Cited by 23 Source ↗Scholar ↗