期刊信息/Journal information
植物表型组学（英文）/Journal Plant PhenomicsCSCDSCI
收录年代
Deep learning in plant phenotyping:the first ten years
Jordan Ubbens;Ian Stavness;Michael P.Pound;Wei Guo1-6
From leaf to canopy:Inversion of lettuce pigment distribution using hyperspectral imaging technology combined with deep learning algorithms
Yue Zhao;Jiangchuan Fan;Xianju Lu;Ying Zhang;Weiliang Wen;Guanmin Huang;Yinglun Li;Xinyu Guo;Liping Chen7-20
Design of a binocular multispectral stereo imaging system and its application in plant phenotyping
Wenxiu Wan;Zhiyuan Liu;Ziru Yu;Jiahui Wang;Xiangyang Yu21-32
IPENS:Interactive unsupervised framework for rapid plant phenotyping extraction via NeRF-SAM2 fusion
Wentao Song;He Huang;Fang Qu;Jiaqi Zhang;Longhui Fang;Yuwei Hao;Chenyang Peng;Youqiang Sun33-46
Establishment of a high-throughput field defoliation data survey strategy combined with genome-wide association studies to reveal the genetic basis of defoliation in cotton
Bowei Xu;Kai Zheng;Liqiang Fan;Zuoren Yang;Le Liu;Rumeng Zhao;Jiajie Yang;Bin Wu;Lili Lu;Xiantao Ai;Jingshan Tian;Fuguang Li47-59
Nondestructive individual tree aboveground biomass estimation using a hierarchical Bayesian approach in combination with individual tree competition indices
Zengrui Zhang;Yuting Zhao;Zhen Zhen;Yinghui Zhao;Jun Li;Yuan Zhou60-72
SegPPD-FS:Segmenting plant pests and diseases in the wild using few-shot learning
Zihan Ge;Xijian Fan;Jingcheng Zhang;Shichao Jin73-86
Three-dimensional reconstruction of densely planted rice seedlings based on MultiView images
Zhigang Zhang;Liwei Wang;Weiqi Ren;Shoutian Dong;Shaowen Liu;Haoran Xu;Yubo Yang;Rui Gao;Zhongbin Su87-104
High-throughput plant phenotyping identifies and discriminates biotic and abiotic stresses in tomato
Maria Isabella Prigigallo;Stephan Summerer;Pasqua Veronico;Francesco Cellini;Marina Tucci;Livia Stavolone;Stefania Grillo;Fabrizio Cillo;Giovanni Bubici;Giorgia Batelli;Antonello Costa;Monica De Palma;Maria Teresa Melillo;Angelo Petrozza;Alessandra Ruggiero;Giorgia Sportelli105-117
DeepSpecN:A new hybrid method combining PROSPECT-PRO and Conv-Transformer to estimate leaf nitrogen content from leaf reflectance
Shuai Yang;Anirudh Belwalkar;Dong Li;Yufeng Ge;Tao Cheng;Fei Wu;Longkang Peng;Daoliang Li;Kang Yu118-134