ResNet incorporating the fusion data of RGB & hyperspectral images improves classification accuracy of vegetable soybean freshness.

ABSTRACT: The freshness of vegetable soybean (VS) is an important indicator for quality evaluation. Currently, deep learning-based image recognition technology provides a fast, efficient, and low-cost method for analyzing the freshness of food. The RGB (red, green, and blue) image recognition technology is widely used in the study of food appearance evaluation. In addition, the hyperspectral image has outstanding performance in predicting the nutrient content of samples. However, there are few reports on the research of classification models based on the fusion data of these two sources of images. We collected RGB and hyperspectral images at four different storage times of VS. The ENVI software was adopted to extract the hyperspectral information, and the RGB images were reconstructed based on the d

SUBMITTER: Bu Y 

PROVIDER: S-EPMC11224382 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature