SUBJECTS : Crop Sciences | Plant Phenotyping | Plant Breeding | Agriculture | Plant Biology | Plant Scienc
LATEST MANUSCRIPTS IN Plant Phenomics
- Cheng Zhang, Jingjing Kong, Daosheng Wu, Zhiyong Guan, Baoqing Ding, Fadi Chen. Wearable Sensor: An Emerging Data Collection Tool for Plant Phenotyping. Plant phenomics (Washington, D.C.). 2023, 5: 0051
Cited : 5Read More - Jonas Anderegg, Radek Zenkl, Achim Walter, Andreas Hund, Bruce A McDonald. Combining High-Resolution Imaging, Deep Learning, and Dynamic Modeling to Separate Disease and Senescence in Wheat Canopies. Plant phenomics (Washington, D.C.). 2023, 5: 0053Cited : 4Read More
- Sally Shuxian Koh, Kapil Dev, Javier Jingheng Tan, Valerie Xinhui Teo, Shuyan Zhang, Dinish U S, Malini Olivo, Daisuke Urano. Classification of Plant Endogenous States Using Machine Learning-Derived Agricultural Indices. Plant phenomics (Washington, D.C.). 2023, 5: 0060Cited : 0Read More
- Qianding Huang, Xingcai Wu, Qi Wang, Xinyu Dong, Yongbin Qin, Xue Wu, Yangyang Gao, Gefei Hao. Knowledge Distillation Facilitates the Lightweight and Efficient Plant Diseases Detection Model. Plant phenomics (Washington, D.C.). 2023, 5: 0062Cited : 1Read More
- Taeko Koji, Hiroyoshi Iwata, Motoyuki Ishimori, Hideki Takanashi, Yuji Yamasaki, Hisashi Tsujimoto. Multispectral Phenotyping and Genetic Analyses of Spring Appearance in Greening Plant, spp. Plant phenomics (Washington, D.C.). 2023, 5: 0063Cited : 1Read More
- Yangmingrui Gao, Yinglun Li, Ruibo Jiang, Xiaohai Zhan, Hao Lu, Wei Guo, Wanneng Yang, Yanfeng Ding, Shouyang Liu. Enhancing Green Fraction Estimation in Rice and Wheat Crops: A Self-Supervised Deep Learning Semantic Segmentation Approach. Plant phenomics (Washington, D.C.). 2023, 5: 0064Cited : 4Read More
- Qiushi Yu, Jingqi Wang, Hui Tang, Jiaxi Zhang, Wenjie Zhang, Liantao Liu, Nan Wang. Application of Improved UNet and EnglightenGAN for Segmentation and Reconstruction of In Situ Roots. Plant phenomics (Washington, D.C.). 2023, 5: 0066Cited : 1Read More
- Wenli Zhang, Yuxin Liu, Chao Zheng, Guoqiang Cui, Wei Guo. EasyDAM_V3: Automatic Fruit Labeling Based on Optimal Source Domain Selection and Data Synthesis via a Knowledge Graph. Plant phenomics (Washington, D.C.). 2023, 5: 0067Cited : 1Read More
- Dominik Rößle, Lukas Prey, Ludwig Ramgraber, Anja Hanemann, Daniel Cremers, Patrick Ole Noack, Torsten Schön. Efficient Noninvasive FHB Estimation using RGB Images from a Novel Multiyear, Multirater Dataset. Plant phenomics (Washington, D.C.). 2023, 5: 0068Cited : 1Read More
- Ruina Zhao, Yujie Guan, Yuqi Lu, Ze Ji, Xiang Yin, Weikuan Jia. FCOS-LSC: A Novel Model for Green Fruit Detection in a Complex Orchard Environment. Plant phenomics (Washington, D.C.). 2023, 5: 0069Cited : 0Read More
- Stefan Paulus, Benjamin Leiding. Can Distributed Ledgers Help to Overcome the Need of Labeled Data for Agricultural Machine Learning Tasks? Plant phenomics (Washington, D.C.). 2023, 5: 0070Cited : 3Read More
- Jinnuo Zhang, Xuping Feng, Jian Jin, Hui Fang. Concise Cascade Methods for Transgenic Rice Seed Discrimination using Spectral Phenotyping. Plant phenomics (Washington, D.C.). 2023, 5: 0071Cited : 1Read More
- John Lagergren, Mirko Pavicic, Hari B Chhetri, Larry M York, Doug Hyatt, David Kainer, Erica M Rutter, Kevin Flores, Jack Bailey-Bale, Marie Klein, Gail Taylor, Daniel Jacobson, Jared Streich. Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in . Plant phenomics (Washington, D.C.). 2023, 5: 0072Cited : 1Read More
- Ting Luo, Xiaoyan Liu, Prakash Lakshmanan. A Combined Genomics and Phenomics Approach is Needed to Boost Breeding in Sugarcane. Plant phenomics (Washington, D.C.). 2023, 5: 0074Cited : 3Read More
- Qingfeng Song, Fusang Liu, Hongyi Bu, Xin-Guang Zhu. Quantifying Contributions of Different Factors to Canopy Photosynthesis in 2 Maize Varieties: Development of a Novel 3D Canopy Modeling Pipeline. Plant phenomics (Washington, D.C.). 2023, 5: 0075Cited : 3Read More
