IV-YOLO:一种基于信息的渐进融合方法,用于准确检测大米
Jianxiang Zhang1, Liexiang Huangfu2, Yanling Zhao1
1College of Agronomy and Horticulture, Jiangsu Vocational College of Agriculture and Forestry, Jurong, Jiangsu, China.
一个新的基于信息旋的渐进融合YOLO (IV-YOLO) 模型增强了在精密农业中的个人大米植物检测. 这种先进的模型有效地分离了附着的植物特征,并减少了背景噪声,以改善监控.
科学领域:
- 农业工程 农业工程
- 计算机视觉 计算机视觉
- 遥感 遥感 遥感 遥感
背景情况:
- 在精密农业中,无人机遥感面临着粘附的米植物特征和背景干扰的挑战.
- 由于这些图像复杂性,传统模型难以以检测单个植物水平的图像.
研究的目的:
- 开发一个先进的深度学习模型,用于准确的个人大米植物检测.
- 在无人机图像中克服现有模型在处理特征粘附和背景杂乱方面的局限性.
主要方法:
- 提出了一个基于信息旋的渐进融合YOLO (IV-YOLO) 模型.
- 引入了一个多尺度螺旋信息旋 (MSIV) 模块,用于特征解和背景解.
- 构建了一个渐进特征融合子 (GFEN) 以实现有效的特征表示.
主要成果:
- 在DRPD数据集上,IV-YOLO模型取得了0.8581的精度.
- 在所有评估指标中表现优于YOLOv5-YOLOv11和FRPNet.
- 在解脱附着特征和减少背景干扰方面表现出卓越的性能.
结论:
- IV-YOLO提供了一个强大的技术解决方案,用于单独监测米植物.
- 该模型通过精确的检测,促进了精密农业的大规模实施.
- 开发的模块有效地解决了基于无人机的农业遥感方面的挑战.
更多相关视频
10:35A Blood-based Test for the Detection of ROS1 and RET Fusion Transcripts from Circulating Ribonucleic Acid Using Digital Polymerase Chain Reaction
Published on: April 5, 2018
09:43Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits
Published on: January 3, 2025
相关概念视频
Nuclear Fusion
A helium nucleus has a mass that is 0.7% less than that of four hydrogen nuclei; this lost mass is converted into energy during the fusion. This reaction produces about...
Methods of Documentation IV: Focus Charting
It typically involves three columns for recording information:
Tumor Progression
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
Effects of EDTA on End-Point Detection Methods
In the visual method, metal-ion indicators (metallochromic dyes), which have distinct colors in their free and complex forms, are added to the mixture to signal the titration's end point. They form stable complexes with metal ions, but these complexes are weaker than the corresponding metal–EDTA complexes. As a...
Tagging and Fusion Proteins
SNAREs and Membrane Fusion
SNAREs exist in pairs that symmetrically interact and catalyze the fusion of the lipid bilayers in vesicle and target organelle. v-SNARE in the vesicle membrane are single polypeptide chains that bind to a complementary t-SNARE, composed of 2...
