Annotated Sugarcane Plants

Published: 25 March 2024| Version 1 | DOI: 10.17632/ydr8vgg64w.1
Talha Ubaid,


Plant annotation is the process of identifying and naming certain aspects or characteristics of plant species, usually for research, categorization, or agriculture. This technique is frequently done out manually by specialists or using automated systems that employ picture recognition technologies. Annotations give useful information on plants' morphology, phenology, diseases, and genetic characteristics. They may include labels for anatomical structures. Annotations may also include categorizing plants based on their development stage, health status, or species identification. Plant annotations are used in agriculture to monitor crop development, detect pests and diseases, optimize cultivation practices, and improve production estimates. Additionally, annotated plant datasets are useful resources for training machine learning models for automated plant recognition and analysis tasks. The images were labeled using the labeling tool "labelImg". The cane under the leaves was labeled. Annotating the images was difficult because the cane section was so little. Labeling needs care and accuracy while drawing a bounded box around the cane. For 175 photos of data, around 18650 bounding boxes were drawn. The bounding boxes were allocated the class name "sugarcane".


Steps to reproduce

1. The use of automated annotation tools to expedite the marking process. 2. Advanced image processing algorithms will be implemented to improve the precision of bounding box delineation. 3. Use data augmentation techniques to diversity and enhance the number of labeled images. 4. Investigation of semantic segmentation for pixel-level annotation of cane sections. 5. Adoption of active learning algorithms to direct manual annotation efforts toward informative photos. 6. Using crowdsourcing platforms to perform distributed annotation tasks. 7. Implementation of feedback tools to continuously assess annotation quality. 8. The creation of domain-specific annotation models adapted to sugarcane plant characteristics.


University of Central Punjab


Annotation, Artificial Intelligence Applications, Sugarcane, Agricultural Research and Development