272 citations
- Sun Yat-sen UniversityCN7 papers
- Zhejiang UniversityCN6 papers
- Singapore University of Technology and DesignSG5 papers
- China Agricultural UniversityCN3 papers
- South China Agricultural UniversityCN3 papers
- Guangdong Province Key Laboratory of Information Security TechnologyCN2 papers
- Ministry of AgricultureCA2 papers
- Northwest A&F UniversityCN2 papers
- Shanghai Institute of Microsystem and Information TechnologyCN2 papers
- Agricultural Information InstituteCN1 paper
- Agritec (Czechia)CZ1 paper
- Amway (United States)US1 paper
20 papers
WHU-STree: A Multi-modal Benchmark Dataset for Street Tree Inventory
Ruifei Ding, Zhe Chen, Wen Fan +5
Street trees are vital to urban livability, providing ecological and social benefits. Establishing a detailed, accurate, and dynamically updated street tree inventory has become es…
Three-dimentional reconstruction of complex, dynamic population canopy architecture for crops with a novel point cloud completion model: A case study in Brassica napus rapeseed
Ziyue Guo, Xin Yang, Yutao Shen +3
Quantitative descriptions of the complete canopy architecture are essential for accurately evaluating crop photosynthesis and yield performance to guide ideotype design. Although v…
PlantSegNeRF: A few-shot, cross-species method for plant 3D instance point cloud reconstruction via joint-channel NeRF with multi-view image instance matching
Xin Yang, Ruiming Du, Hanyang Huang +7
Organ segmentation of plant point clouds is a prerequisite for the high-resolution and accurate extraction of organ-level phenotypic traits. Although the fast development of deep l…
Smartphone-integrated RPA-CRISPR-Cas12a Detection System with Microneedle Sampling for Point-of-Care Diagnosis of Potato Late Blight in Early Stage
Jiangnan Zhao, Hanbo Xu, Cifu Xu +4
Potato late blight, caused by the oomycete pathogen Phytophthora infestans, is one of the most devastating diseases affecting potato crops in the history. Although conventional det…
Soybean pod and seed counting in both outdoor fields and indoor laboratories using unions of deep neural networks
Tianyou Jiang, Mingshun Shao, Tianyi Zhang +2
Automatic counting soybean pods and seeds in outdoor fields allows for rapid yield estimation before harvesting, while indoor laboratory counting offers greater accuracy. Both meth…
Biomass phenotyping of oilseed rape through UAV multi-view oblique imaging with 3DGS and SAM model
Yutao Shen, Hongyu Zhou, Xin Yang +5
Biomass estimation of oilseed rape is crucial for optimizing crop productivity and breeding strategies. While UAV-based imaging has advanced high-throughput phenotyping, current me…