# WRA: A 2.2-to-6.3 TOPS Highly Unified Dynamically Reconfigurable Accelerator Using a Novel Winograd Decomposition Algorithm for Convolutional Neural Networks

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/wra-a-2-2-to-6-3-tops-highly-unified-dynamically-reconfigurable-accelerator/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Chen Yang,Yizhou Wang,Xiaoli Wang,Li Geng |
| Citations | 45 |
| DOI | 10.1109/tcsi.2019.2928682 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2964525696 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Yizhou Wang](https://scholariq.org/researchers/yizhou-wang/)

## Paper primary topic

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

## Paper topics

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [CCD and CMOS Imaging Sensors](https://scholariq.org/topics/ccd-and-cmos-imaging-sensors/)
- [Advanced Memory and Neural Computing](https://scholariq.org/topics/advanced-memory-and-neural-computing/)

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