StomataSeg: Semi-Supervised Instance Segmentation for Sorghum Stomatal Components

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Authors: Zhongtian Huang
Cited by: 0

Abstract

The primary distribution of this Sorghum Stomata Dataset(StomataSeg) is patch-based: the original patches are stored inside the original_patches/ directory, and the pseudo labels patches are stored inside the pseudo_labels_patches/ directory. For completeness and reproducibility, the original full-resolution microscope images and their original COCO annotation files are provided as supplementary material in original_images/. Each split (train/val/test) includes matching COCO-style JSON annotations with three instance classes (pore area, guard cell area, complex area).

Fields of Study & Subjects

Smart Agriculture and AI Advanced Neural Network Applications Cell Image Analysis Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 January 2026
Document type
Dataset