Self-Supervised Maize Kernel Classification and Segmentation for Embryo Identification

These are companion data of manuscript "Self-Supervised Maize Kernel Classification and Segmentation for Embryo Identification" that was submitted to Frontiers in Plant Science. The data is organized into three main folders: 'class_full_imgs', 'seg_full_imgs', and 'unlabeled'.
The 'class_full_imgs' folder contains labeled data used to train the classification model, which is divided into train, validation, and test subfolders. Each of these subfolders contains 'oriented' and 'non-oriented' images.
The 'seg_full_imgs' folder contains labeled data used to train the segmentation model. The 'InputImages' subfolder contains raw images, and the 'OutputImages' subfolder contains the segmented images.
The 'unlabeled' folder contains images without any labels. These images were used for self-supervised pretraining of classification and segmentation models.