UAV Detection: A STDP trained Deep Convolutional Spiking Neural Network Retina-Neuromorphic Approach
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Abstract (arXiv)
The Dynamic Vision Sensor (DVS) has many attributes that allow it to be well suited to the task for UAV Detection. This paper is the first to look at exploiting the features of an Event Camera solely for Drone Detection while combining it with a Spiking Neural Network (SNN) trained using the unsupervised approach of Spike-Time-Dependent Plasticity (STDP) for feature and pattern recognition for detection. Highlighting the key features and current drawbacks with the technology while comparing real and simulated data to show how future devices could overcome these drawbacks to help tackle this current problem.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Apr 2019.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 2.
4 papers.
- 2022Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Surveycited by 28
- 2025Drone Detection with Event Camerascited by 9
- 2025Drone Detection Using a Low-Power Neuromorphic Virtual Tripwirecited by 2
- 2021Unsupervised Spiking Instance Segmentation on Event Data using STDPcited by 1
- 2025Drone Detection Using a Low-Power Neuromorphic Virtual Tripwire16 Sep 2025
- 2025Drone Detection with Event Cameras6 Aug 2025
- 2022Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey7 Nov 2022
- 2021Unsupervised Spiking Instance Segmentation on Event Data using STDP9 Nov 2021