Summary of Neuronal Competition Groups with Supervised Stdp For Spike-based Classification, by Gaspard Goupy and Pierre Tirilly and Ioan Marius Bilasco
Neuronal Competition Groups with Supervised STDP for Spike-Based Classification
by Gaspard Goupy, Pierre Tirilly, Ioan Marius Bilasco
First submitted to arxiv on: 22 Oct 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a novel approach to training Spiking Neural Networks (SNNs) using Spike Timing-Dependent Plasticity (STDP) on neuromorphic hardware. The authors introduce the Neuronal Competition Group (NCG), an architecture that enables effective Winner-Takes-All (WTA) competition in supervised STDP classification. By combining first-spike coding and supervised STDP training, the NCG improves classification capabilities by promoting the learning of various patterns per class. Experiments on image recognition datasets such as CIFAR-10 and CIFAR-100 demonstrate significant accuracy improvements using state-of-the-art supervised STDP rules and two different unsupervised feature extractors. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about a new way to train special types of computers called Spiking Neural Networks (SNNs). These computers are inspired by how our brains work, but they’re still not as good at learning things on their own. The researchers came up with a new idea to make the SNNs better at recognizing pictures and other tasks. They created something called Neuronal Competition Group (NCG) that helps the SNNs focus on different patterns in the pictures and get better at telling them apart. |
Keywords
» Artificial intelligence » Classification » Supervised » Unsupervised
