# Trainable Spiking-YOLO for low-latency and high-performance object detection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/trainable-spiking-yolo-for-low-latency-and-high-performance-object-detection/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Mengwen Yuan,Chengjun Zhang,Ziming Wang,Huixiang Liu,Gang Pan,Huajin Tang |
| Citations | 40 |
| DOI | 10.1016/j.neunet.2023.106092 |
| Fields | Engineering,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4390278394 |
| PMID | 38211460 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Mengwen Yuan](https://scholariq.org/researchers/mengwen-yuan/)

## Paper journal

- [Neural Networks](https://scholariq.org/journals/neural-networks/)

## Paper primary topic

- [Advanced Memory and Neural Computing](https://scholariq.org/topics/advanced-memory-and-neural-computing/)

## Paper topics

- [Advanced Memory and Neural Computing](https://scholariq.org/topics/advanced-memory-and-neural-computing/)
- [Ferroelectric and Negative Capacitance Devices](https://scholariq.org/topics/ferroelectric-and-negative-capacitance-devices/)
- [Neural dynamics and brain function](https://scholariq.org/topics/neural-dynamics-and-brain-function/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.