Self-Supervised Maize Kernel Classification and Segmentation for Embryo Identification
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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'. <br> 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. <br> 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. <br> The 'unlabeled' folder contains images without any labels. These images were used for self-supervised pretraining of classification and segmentation models.
