Paul Kirkland

Orcid: 0000-0001-5905-6816

According to our database1, Paul Kirkland authored at least 15 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
Exploring Spiking Neural Networks (SNN) for Low Size, Weight, and Power (SWaP) Benefits.
Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

2023
Neuromorphic Sensing and Processing for Space Domain Awareness.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

Frameworks for SNNs: A Review of Data Science-Oriented Software and an Expansion of SpykeTorch.
Proceedings of the Engineering Applications of Neural Networks, 2023

2022
Keys to accurate feature extraction using residual spiking neural networks.
Neuromorph. Comput. Eng., December, 2022

Simple and complex spiking neurons: perspectives and analysis in a simple STDP scenario.
Neuromorph. Comput. Eng., December, 2022

Unsupervised Spiking Instance Segmentation on Event Data Using STDP Features.
IEEE Trans. Computers, 2022

Evaluating the temporal understanding of neural networks on event-based action recognition with DVS-Gesture-Chain.
CoRR, 2022

2021
Unsupervised Spiking Instance Segmentation on Event Data using STDP.
CoRR, 2021

Ultrafast Neuromorphic Photonic Image Processing with a VCSEL Neuron.
CoRR, 2021

2020
Less is more: the neuromorphic engineering advantage
PhD thesis, 2020

Perception Understanding Action: Adding Understanding to the Perception Action Cycle With Spiking Segmentation.
Frontiers Neurorobotics, 2020

SpikeSEG: Spiking Segmentation via STDP Saliency Mapping.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019
CubeSat-Based Passive Bistatic Radar for Space Situational Awareness: A Feasibility Study.
IEEE Trans. Aerosp. Electron. Syst., 2019

UAV Detection: A STDP Trained Deep Convolutional Spiking Neural Network Retina-Neuromorphic Approach.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019

2018
Real-Time Embedded Intelligence System: Emotion Recognition on Raspberry Pi with Intel NCS.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018


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