Toward Real Scenery: A Lightweight Tomato Growth Inspection Algorithm for Leaf Disease Detection and Fruit Counting [0.03%]
面向实景的轻量型番茄生长检测算法（叶片疾病检测与果实计数）
Rui Kang,Jiaxin Huang,Xuehai Zhou et al.
Rui Kang et al.
The deployment of intelligent surveillance systems to monitor tomato plant growth poses substantial challenges due to the dynamic nature of disease patterns and the complexity of environmental conditions such as background and lighting. In ...
A Multi-Target Regression Method to Predict Element Concentrations in Tomato Leaves Using Hyperspectral Imaging [0.03%]
基于高光谱图像的番茄叶片元素浓度预测方法研究
Andrés Aguilar Ariza,Naoyuki Sotta,Toru Fujiwara et al.
Andrés Aguilar Ariza et al.
Recent years have seen the development of novel, rapid, and inexpensive techniques for collecting plant data to monitor the nutritional status of crops. These techniques include hyperspectral imaging, which has been widely used in combinati...
Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data [0.03%]
基于激光雷达数据和三维辐射传输模型的种植林光合有效辐射（APAR）精细定量研究
Xun Zhao,Jianbo Qi,Zhexiu Yu et al.
Xun Zhao et al.
Quantifying the relationship between light and stands or individual trees is of great significance in understanding tree competition, improving forest productivity, and comprehending ecological processes. However, accurately depicting the s...
DC2Net: An Asian Soybean Rust Detection Model Based on Hyperspectral Imaging and Deep Learning [0.03%]
基于高光谱图像和深度学习的亚洲大豆锈病检测模型 DC2Net
Jiarui Feng,Shenghui Zhang,Zhaoyu Zhai et al.
Jiarui Feng et al.
Asian soybean rust (ASR) is one of the major diseases that causes serious yield loss worldwide, even up to 80%. Early and accurate detection of ASR is critical to reduce economic losses. Hyperspectral imaging, combined with deep learning, h...
Geographic-Scale Coffee Cherry Counting with Smartphones and Deep Learning [0.03%]
基于智能手机和深度学习的地理规模咖啡樱桃计数技术
Juan Camilo Rivera Palacio,Christian Bunn,Eric Rahn et al.
Juan Camilo Rivera Palacio et al.
Deep learning and computer vision, using remote sensing and drones, are 2 promising nondestructive methods for plant monitoring and phenotyping. However, their applications are infeasible for many crop systems under tree canopies, such as c...
Microfluidic Device for Simple Diagnosis of Plant Growth Condition by Detecting miRNAs from Filtered Plant Extracts [0.03%]
基于微流控芯片的植物miRNA快速检测及生长状态简易诊断方法
Yaichi Kawakatsu,Ryo Okada,Mitsuo Hara et al.
Yaichi Kawakatsu et al.
Plants are exposed to a variety of environmental stress, and starvation of inorganic phosphorus can be a major constraint in crop production. In plants, in response to phosphate deficiency in soil, miR399, a type of microRNA (miRNA), is up-...
PAT (Periderm Assessment Toolkit): A Quantitative and Large-Scale Screening Method for Periderm Measurements [0.03%]
用于皮层测量的定量和大规模筛选方法(PAT)
Gonzalo Villarino,Signe Dahlberg-Wright,Ling Zhang et al.
Gonzalo Villarino et al.
The periderm is a vital protective tissue found in the roots, stems, and woody elements of diverse plant species. It plays an important function in these plants by assuming the role of the epidermis as the outermost layer. Despite its criti...
Channel Attention GAN-Based Synthetic Weed Generation for Precise Weed Identification [0.03%]
基于通道注意力GAN的合成杂草生成用于精确杂草识别
Tang Li,Motoaki Asai,Yoichiro Kato et al.
Tang Li et al.
Weed is a major biological factor causing declines in crop yield. However, widespread herbicide application and indiscriminate weeding with soil disturbance are of great concern because of their environmental impacts. Site-specific weed man...
Maturity Classification of Rapeseed Using Hyperspectral Image Combined with Machine Learning [0.03%]
基于高光谱图像的机器学习油菜成熟度分类
Hui Feng,Yongqi Chen,Jingyan Song et al.
Hui Feng et al.
Oilseed rape is an important oilseed crop planted worldwide. Maturity classification plays a crucial role in enhancing yield and expediting breeding research. Conventional methods of maturity classification are laborious and destructive in ...
Time-Series Field Phenotyping of Soybean Growth Analysis by Combining Multimodal Deep Learning and Dynamic Modeling [0.03%]
基于多模态深度学习与动态模型结合的 soybean 生长时序表型分析
Hui Yu,Lin Weng,Songquan Wu et al.
Hui Yu et al.
The rate of soybean canopy establishment largely determines photoperiodic sensitivity, subsequently influencing yield potential. However, assessing the rate of soybean canopy development in large-scale field breeding trials is both laboriou...