How Optical Sensors and Deep Learning Enhance the Production Management in Smart Agriculture
The advent of smart agriculture marks a paradigm shift from experience-driven to data-driven decision-making, fundamentally reshaping centuries-old farming practices [...]
Authors
- Fenghua Yu (ORCID: https://orcid.org/0000-0001-6545-9873)
- Jibo Yue (ORCID: https://orcid.org/0000-0001-9766-5313)
- Meiyan Shu (ORCID: https://orcid.org/0000-0002-1519-5520)
- Chengquan Zhou (ORCID: https://orcid.org/0000-0001-7427-0888)
- Haikuan Feng (ORCID: https://orcid.org/0000-0003-3312-6200)
Institutions
- Shenyang Agricultural University (CN)
- Hangzhou Academy of Agricultural Sciences (CN)
- ZheJiang Academy of Agricultural Sciences (CN)
- National Engineering Research Center for Information Technology in Agriculture (CN)
- Henan Agricultural University (CN)
Publication Details
- Journal
- Agriculture
- Published
- 2025-12-17
- DOI
- https://doi.org/10.3390/agriculture15242612
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00