# Online Few-shot Gesture Learning on a Neuromorphic Processor

arXiv: https://arxiv.org/abs/2008.01151 · HTML: https://mlsanity.com/paper/2008.01151/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Aug 2020.

## Built on by (most cited first, 18 of 18)

- [CarSNN: An Efficient Spiking Neural Network for Event-Based Autonomous Cars on the Loihi Neuromorphic Research Processor](https://mlsanity.com/paper/2107.00401/) (2021)
- [Enabling hand gesture customization on wrist-worn devices](https://mlsanity.com/paper/2203.15239/) (2022)
- [Meta-learning Spiking Neural Networks with Surrogate Gradient Descent](https://mlsanity.com/paper/2201.10777/) (2022)
- [Fast On-Device Adaptation for Spiking Neural Networks via Online-Within-Online Meta-Learning](https://mlsanity.com/paper/2103.03901/) (2021)
- [Encoding Event-Based Data With a Hybrid SNN Guided Variational Auto-encoder in Neuromorphic Hardware](https://mlsanity.com/paper/2104.00165/) (2021)
- [WatchGuardian: Enabling User-Defined Personalized Just-in-Time Intervention on Smartwatch](https://mlsanity.com/paper/2502.05783/) (2025)
- [12 mJ per Class On-Device Online Few-Shot Class-Incremental Learning](https://mlsanity.com/paper/2403.07851/) (2024)
- [Learning to learn online with neuromodulated synaptic plasticity in spiking neural networks](https://mlsanity.com/paper/2206.12520/) (2022)
- [Augmenting learning in neuro-embodied systems through neurobiological first principles](https://mlsanity.com/paper/2407.04525/) (2024)
- [Improving the adaptive and continuous learning capabilities of artificial neural networks: Lessons from multi-neuromodulatory dynamics](https://mlsanity.com/paper/2501.06762/) (2025)
- [A Dual-Memory Architecture for Reinforcement Learning on Neuromorphic Platforms](https://mlsanity.com/paper/2103.04780/) (2021)
- [Efficient Gesture Recognition on Spiking Convolutional Networks Through Sensor Fusion of Event-Based and Depth Data](https://mlsanity.com/paper/2401.17064/) (2024)
- [Wearable Sensor-Based Few-Shot Continual Learning on Hand Gestures for Motor-Impaired Individuals via Latent Embedding Exploitation](https://mlsanity.com/paper/2405.08969/) (2024)
- [Emulating Brain-like Rapid Learning in Neuromorphic Edge Computing](https://mlsanity.com/paper/2408.15800/) (2024)
- [Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning](https://mlsanity.com/paper/2505.07921/) (2025)
- [Online Continual Learning on Intel Loihi 2 via a Co-designed Spiking Neural Network](https://mlsanity.com/paper/2511.01553/) (2025)
- [Neuromorphic visual attention for Sign-language recognition on SpiNNaker](https://mlsanity.com/paper/2605.06005/) (2026)
- [CLANE: Continual Learning of Actions on Neuromorphic Hardware from Event Cameras](https://mlsanity.com/paper/2605.28387/) (2026)

## Abstract (arXiv)

We present the Surrogate-gradient Online Error-triggered Learning (SOEL) system for online few-shot learning on neuromorphic processors. The SOEL learning system uses a combination of transfer learning and principles of computational neuroscience and deep learning. We show that partially trained deep Spiking Neural Networks (SNNs) implemented on neuromorphic hardware can rapidly adapt online to new classes of data within a domain. SOEL updates trigger when an error occurs, enabling faster learning with fewer updates. Using gesture recognition as a case study, we show SOEL can be used for online few-shot learning of new classes of pre-recorded gesture data and rapid online learning of new gestures from data streamed live from a Dynamic Active-pixel Vision Sensor to an Intel Loihi neuromorphic research processor.