PRS2Net: an efficient intelligent carrot detection model via filter pruning and attention mechanisms
This approach enhances the speed and efficiency of carrot quality evaluation, offering a practical, resource-efficient solution for real-world applications in agriculture and food industries, potentially reducing operational costs and improving scalability for automated systems. © 2025 Society of Chemical Industry.
Authors
- Limiao Deng (ORCID: https://orcid.org/0000-0003-1878-3034)
- Hongfei Zhu (ORCID: https://orcid.org/0000-0001-5103-5746)
- Xuetong Zhai (ORCID: https://orcid.org/0000-0002-2618-5686)
- Yifan Zhao (ORCID: https://orcid.org/0000-0003-2383-5724)
- Cong Wang (ORCID: https://orcid.org/0009-0004-3865-1033)
- Hang Liu (ORCID: https://orcid.org/0000-0001-6323-7388)
- Zhongzhi Han (ORCID: https://orcid.org/0000-0002-5662-319X)
- Yanshen Zhao
- Huayu Fu
Institutions
- Qingdao Agricultural University (CN)
- Hainan University (CN)
Publication Details
- Journal
- Journal of the Science of Food and Agriculture
- Published
- 2025-08-22
- DOI
- https://doi.org/10.1002/jsfa.70142
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China