Improving fine-grained food classification using deep residual learning and selective state space models
We pioneer the integration of a residual learning framework within the VMamba model to concurrently harness both global and local state features. The code can be obtained on GitHub: https://github.com/ChiShengChen/ResVMamba.
Authors
- Chi-Sheng Chen (ORCID: https://orcid.org/0000-0003-0807-0217)
- Shao-Hsuan Chang (ORCID: https://orcid.org/0000-0003-4136-7928)
- Di Jiang (ORCID: https://orcid.org/0000-0003-1676-4868)
- Guanying Chen (ORCID: https://orcid.org/0000-0002-1273-4752)
- Dai-Shi Chen (ORCID: https://orcid.org/0000-0002-0276-5678)
- Dong Zhou
Institutions
- University of Liverpool (GB)
- National Taiwan University (TW)
- ShenZhen People’s Hospital (CN)
- Dongguan People’s Hospital (CN)
- Neurological Surgery (US)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1371/journal.pone.0322695
- Citations
- 4
- Primary Topic
- Advanced Chemical Sensor Technologies
- Type
- article
- Field-Weighted Citation Impact
- 2.70