ArticleFrontiers in plant science2020
Investigation on Data Fusion of Multisource Spectral Data for Rice Leaf Diseases Identification Using Machine Learning Methods.
Article in Frontiers in plant science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Spectroscopic technologies and data fusion: Applications for the dairy industry.Frontiers in nutrition · 2022Pooled it
- Neural Network-Based Study for Rice Leaf Disease Recognition and Classification: A Comparative Analysis Between Feature-Based Model and Direct Imaging Model.Food science & nutrition · 2025Article
- Early detection of soybean mosaic virus using portable Raman spectroscopy coupled with machine learning.Frontiers in plant science · 2025Article
- Harnessing artificial intelligence for sustainable rice leaf disease classification.Frontiers in plant science · 2025Article
- An intelligent identification for pest and disease detection in wheat leaf based on environmental data using multimodal data fusion.Frontiers in plant science · 2025Article
- Early diagnosis of Cladosporium fulvum in greenhouse tomato plants based on visible/near-infrared (VIS/NIR) and near-infrared (NIR) data fusion.Scientific reports · 2024Article
- YOLOv8-RMDA: Lightweight YOLOv8 Network for Early Detection of Small Target Diseases in Tea.Sensors (Basel, Switzerland) · 2024Article
- DCPlant phenomics (Washington, D.C.) · 2024Article
- Discrimination of leaf diseases in Maize/Soybean intercropping system based on hyperspectral imaging.Frontiers in plant science · 2024Article
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- Discrimination of Deoxynivalenol Levels of Barley Kernels Using Hyperspectral Imaging in Tandem with Optimized Convolutional Neural Network.Sensors (Basel, Switzerland) · 2023Article
- Diagnosis and application of rice diseases based on deep learning.PeerJ. Computer science · 2023Article
- Dual-branch collaborative learning network for crop disease identification.Frontiers in plant science · 2023Article
- Spectral characterization and severity assessment of rice blast disease using univariate and multivariate models.Frontiers in plant science · 2023Article
- Convolution Neural Network with Laser-Induced Breakdown Spectroscopy as a Monitoring Tool for Laser Cleaning Process.Sensors (Basel, Switzerland) · 2022Article
- Challenges and Opportunities of Implementing Data Fusion in Process Analytical Technology-A Review.Molecules (Basel, Switzerland) · 2022Review
- Rice bacterial blight resistant cultivar selection based on visible/near-infrared spectrum and deep learning.Plant methods · 2022Article
- Effects of Image Dataset Configuration on the Accuracy of Rice Disease Recognition Based on Convolution Neural Network.Frontiers in plant science · 2022Article
- Study on the Classification Method of Rice Leaf Blast Levels Based on Fusion Features and Adaptive-Weight Immune Particle Swarm Optimization Extreme Learning Machine Algorithm.Frontiers in plant science · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rice diseases are major threats to rice yield and quality. Rapid and accurate detection of rice diseases is of great importance for precise disease prevention and treatment. Various spectroscopic techniques have been used to detect plant diseases. To rapidly and accurately detect three different rice diseases [leaf blight (
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Registered trials
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