1. Digitized specimens are an indispensable resource for rapidly acquiring big datasets and typically must be preprocessed prior to conducting analyses. One crucial image preprocessing step in any ima
The quantification and identification of components in archaeological micromorphology remain subjective and challenging, particularly for early-career researchers. To address this, we developed a deep
Image data and trained deep learning models to segment the epithelium / Ki67 positive or negative nuclei in haematoxylin/DAB immunohistochemistry images. As described in our manuscript entitled: Devel
Dataset includes raw specimen images, ground truth masks and Deep Lab predicted masks. Also included are flat CSV files of ground truth and Deep Lab predicted coordinates.AbstractUltraviolet colourati
The root system of corn, as the underground part of plants, has a crucial impact on crop growth and yield. A deep understanding of the growth characteristics and phenotypic features of spring maize ro
