Analyzing Changes in Maize Leaves Orientation due to GxExM Using an Automatic Method from RGB Images [0.03%]
基于RGB图像的自动方法分析GxExM对玉米叶片方位变化的影响
Mario Serouart,Raul Lopez-Lozano,Gaëtan Daubige et al.
Mario Serouart et al.
The sowing pattern has an important impact on light interception efficiency in maize by determining the spatial distribution of leaves within the canopy. Leaves orientation is an important architectural trait determining maize canopies ligh...
A Mechanistic Model for Estimating Rice Photosynthetic Capacity and Stomatal Conductance from Sun-Induced Chlorophyll Fluorescence [0.03%]
基于太阳诱导的叶绿素荧光估计水稻光合能力及气孔导度的机理模型
Hao Ding,Zihao Wang,Yongguang Zhang et al.
Hao Ding et al.
Enhancing the photosynthetic rate is one of the effective ways to increase rice yield, given that photosynthesis is the basis of crop productivity. At the leaf level, crops' photosynthetic rate is mainly determined by photosynthetic functio...
A Novel Feature Selection Strategy Based on Salp Swarm Algorithm for Plant Disease Detection [0.03%]
一种基于海绵群算法的植物病害检测新型特征选择策略
Xiaojun Xie,Fei Xia,Yufeng Wu et al.
Xiaojun Xie et al.
Deep learning has been widely used for plant disease recognition in smart agriculture and has proven to be a powerful tool for image classification and pattern recognition. However, it has limited interpretability for deep features. With th...
An Effective Image-Based Tomato Leaf Disease Segmentation Method Using MC-UNet [0.03%]
一种有效的基于图像的番茄叶病害分割方法MC-UNet
Yubao Deng,Haoran Xi,Guoxiong Zhou et al.
Yubao Deng et al.
Tomato disease control is an urgent requirement in the field of intellectual agriculture, and one of the keys to it is quantitative identification and precise segmentation of tomato leaf diseases. Some diseased areas on tomato leaves are ti...
Assessing the Storage Root Development of Cassava with a New Analysis Tool [0.03%]
一个新的分析工具在木薯储藏根发育评估中的应用
Jens Wilhelm,Tobias Wojciechowski,Johannes A Postma et al.
Jens Wilhelm et al.
Storage roots of cassava plants crops are one of the main providers of starch in many South American, African, and Asian countries. Finding varieties with high yields is crucial for growing and breeding. This requires a better understanding...
Multi-Source Data Fusion Improves Time-Series Phenotype Accuracy in Maize under a Field High-Throughput Phenotyping Platform [0.03%]
多数据源融合提高玉米高通量表型平台下的时间序列表型准确性
Yinglun Li,Weiliang Wen,Jiangchuan Fan et al.
Yinglun Li et al.
The field phenotyping platforms that can obtain high-throughput and time-series phenotypes of plant populations at the 3-dimensional level are crucial for plant breeding and management. However, it is difficult to align the point cloud data...
Self-Supervised Plant Phenotyping by Combining Domain Adaptation with 3D Plant Model Simulations: Application to Wheat Leaf Counting at Seedling Stage [0.03%]
结合领域适应与三维作物模型模拟的自监督作物表型研究——以小麦苗期叶数计算为例
Yinglun Li,Xiaohai Zhan,Shouyang Liu et al.
Yinglun Li et al.
The number of leaves at a given time is important to characterize plant growth and development. In this work, we developed a high-throughput method to count the number of leaves by detecting leaf tips in RGB images. The digital plant phenot...
Process-Based Crop Modeling for High Applicability with Attention Mechanism and Multitask Decoders [0.03%]
基于注意力机制和多任务解码器的高适用性过程作物模型
Taewon Moon,Dongpil Kim,Sungmin Kwon et al.
Taewon Moon et al.
Crop models have been developed for wide research purposes and scales, but they have low compatibility due to the diversity of current modeling studies. Improving model adaptability can lead to model integration. Since deep neural networks ...
PDDD-PreTrain: A Series of Commonly Used Pre-Trained Models Support Image-Based Plant Disease Diagnosis [0.03%]
基于图像的植物病害诊断常用预训练模型系列PDDD-PreTrain
Xinyu Dong,Qi Wang,Qianding Huang et al.
Xinyu Dong et al.
Plant diseases threaten global food security by reducing crop yield; thus, diagnosing plant diseases is critical to agricultural production. Artificial intelligence technologies gradually replace traditional plant disease diagnosis methods ...
High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Method to Segment Overlapping Plants [0.03%]
高通量田间表型组学：一种自监督的序列CNN方法对重叠植物进行分割
Xingche Guo,Yumou Qiu,Dan Nettleton et al.
Xingche Guo et al.
High-throughput plant phenotyping-the use of imaging and remote sensing to record plant growth dynamics-is becoming more widely used. The first step in this process is typically plant segmentation, which requires a well-labeled training dat...