Hyperspectral imaging (HSI) has been effectively used in the nondestructive assessment of food quality in recent years. However, the identification of moldy objects using HSIs still faces challenges, including slow detection speed and poor identification accuracy. To address these challenges, this study proposes a three-dimensional hyperspectral mold detection (3D-HMD) approach. The model utilizes multiple 3D convolution (3DMC) modules as the backbone network for optimizing spectral-spatial feature extraction and introduces an attention mechanism to promote the feature information of different...
