返回
Multimodal fusion-based classification method for small-sample imperfect wheat kernels using hyperspectral imaging
DOI:10.1016/j.foodcont.2026.112034.png)
摘要
En 中文
• 基于深度学习框架的小麦质量检测。
• 该模型基于小样本高光谱数据进行分类。
• 小麦质量检测验证:多模态融合数据与机器学习。
• 利用小样本数据实现小麦质量检测的高精度。
Keyword:
Deep learning
Hyperspectral imaging
Wheat quality detection
Small-sample data
Multimodal fusion
期刊
IF:
6.3
论文数:
1.2W
被引数:
4.0W
机构
暂无机构信息
引用论文
Determination of wheat kernels damaged by Fusarium head blight using monochromatic images of effective wavelengths from hyperspectral imaging coupled with an architecture self-search deep network
FOOD CONTROL
IF6.3
Soybean yield prediction from UAV using multimodal data fusion and deep learning基于多模态数据融合和深度学习的无人机大豆产量预测
Near-infrared hyperspectral imaging evaluation of Fusarium damage and DON in single wheat kernels
FOOD CONTROL
IF6.3

