DAFFnet: Seed classification of soybean variety based on dual attention feature fusion networks

Rapid, accurate seed classification of soybean varieties is needed for product quality control. We describe a hyperspectral image-based deep-learning model called Dual Attention Feature Fusion Networks (DAFFnet), which sequentially applies 3D Convolutional Neural Network (CNN) and 2D CNN. A fusion attention mechanism module in 2D CNN permits the model to capture local and global feature information by combining with Convolution Block Attention Module (CBAM) and Mobile Vision Transformer (MViT), outperforming conventional hyperspectral image classification models in seed classification.