# Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-attention-based-spatially-recursive-networks-for-fine-grained-visual/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Lin Wu,Yang Wang,Xue Li,Junbin Gao |
| Citations | 256 |
| DOI | 10.1109/tcyb.2018.2813971 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2791779647 |
| PMID | 29993796 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Xue Li](https://scholariq.org/researchers/xue-li/)

## Paper journal

- [IEEE Transactions on Cybernetics](https://scholariq.org/journals/ieee-transactions-on-cybernetics/)

## 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/)
- [Video Surveillance and Tracking Methods](https://scholariq.org/topics/video-surveillance-and-tracking-methods/)
- [Visual Attention and Saliency Detection](https://scholariq.org/topics/visual-attention-and-saliency-detection/)

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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.