中国水稻科学2026，Vol.40Issue(5)：663-678,16.DOI:10.16819/j.1001-7216.2026.250703
基于多模态融合的水稻生育期智能识别方法
Intelligent Recognition Method of Rice Growth Stage Based on Multimodal Fusion
摘要
Abstract
[Objective]The growth period of rice is an important reference indicator for irrigation,fertilization,and pest control measures in rice planting management.Researching an intelligent recognition method for rice growth period based on multimodal fusion,improving the accuracy of rice growth period recognition,is of great significance for optimizing rice planting management measures and increasing rice yield.[Method]To address the vulnerability of RGB images to lighting,an H-color channel image is extracted,and a dual-branch rice growth stage image recognition model based on residual network and attention mechanism is established;Due to the influence of meteorological factors on the length of rice growth period,a rice growth period meteorological identification model based on three meteorological factors and a bidirectional long-short period network is established;Using decision trees for decision-level multimodal feature fusion,multiple models were trained and tested on a self-built rice growth period dataset.[Result]The improved rice growth period image recognition model achieved an accuracy of 84.25%,which is superior to traditional image recognition models such as ResNet50 and ConvNeXt.The multi-modality model based on images and meteorological achieved an accuracy of 87.66%in identifying 9 rice growth stages,which is superior to the single modality recognition model based on images and meteorology.[Conclusion]The multimodal recognition model based on image and meteorological fusion compensates for the shortcomings of single modal recognition methods.Compared with single modal recognition models,it has significantly improved the accuracy of identifying 9 rice growth stages.关键词
水稻生育期/多模态融合/图像模态/气象模态/决策树Key words
rice growth period/multimodal/image modality/meteorological modality/decision tree引用本文复制引用
许永炜,刘淑华,冯泽霖,罗举,倪兆新,杨保军,姚青,李阿根..基于多模态融合的水稻生育期智能识别方法[J].中国水稻科学,2026,40(5):663-678,16.基金项目
浙江省"三农九方"科技协作计划项目(2024SNJF010) （2024SNJF010）
浙江省农业重大技术协同推广计划项目(2023ZDXT01-5). （2023ZDXT01-5）
