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20212026
most citedSpiking Neural Networks for Visual Place Recognition via Weighted Neuronal Assignments

29 citations · 46 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Removing the Compute Bottleneck for Event-based Visual Place Recognition with Spiking Neural Networks

Somayeh Hussaini, Tobias Fischer, Michael Milford

Neuromorphic sensing and computing promise low latency and high energy efficiency for robotics, yet most event-based visual place recognition (VPR) pipelines reintroduce dense, fra…

cs.CV2026

Automatic Map Density Selection for Locally-Performant Visual Place Recognition

Somayeh Hussaini, Tobias Fischer, Michael Milford

A key challenge in translating Visual Place Recognition (VPR) from the lab to long-term deployment is ensuring a priori that a system can meet user-specified performance requiremen…

cs.CV2025

Improving Visual Place Recognition with Sequence-Matching Receptiveness Prediction

Somayeh Hussaini, Tobias Fischer, Michael Milford

In visual place recognition (VPR), filtering and sequence-based matching approaches can improve performance by integrating temporal information across image sequences, especially i…

cs.CV2024

A Hyperdimensional One Place Signature to Represent Them All: Stackable Descriptors For Visual Place Recognition

Connor Malone, Somayeh Hussaini, Tobias Fischer +1

Visual Place Recognition (VPR) enables coarse localization by comparing query images to a reference database of geo-tagged images. Recent breakthroughs in deep learning architectur…

cs.CV2023★ 17 cited

Applications of Spiking Neural Networks in Visual Place Recognition

Somayeh Hussaini, Michael Milford, Tobias Fischer

In robotics, Spiking Neural Networks (SNNs) are increasingly recognized for their largely-unrealized potential energy efficiency and low latency particularly when implemented on ne…

cs.CV2022

Ensembles of Compact, Region-specific & Regularized Spiking Neural Networks for Scalable Place Recognition

Somayeh Hussaini, Michael Milford, Tobias Fischer

Spiking neural networks have significant potential utility in robotics due to their high energy efficiency on specialized hardware, but proof-of-concept implementations have not ye…

cs.CV2021★ 29 cited

Spiking Neural Networks for Visual Place Recognition via Weighted Neuronal Assignments

Somayeh Hussaini, Michael Milford, Tobias Fischer

Spiking neural networks (SNNs) offer both compelling potential advantages, including energy efficiency and low latencies and challenges including the non-differentiable nature of e…