# Volume and leaf area calculation of cabbage with a neural network-based instance segmentation

arXiv: https://arxiv.org/abs/2104.05284 · HTML: https://mlsanity.com/paper/2104.05284/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 16 references that are in the map.
- First posted on arXiv 12 Apr 2021.

## Built on by (most cited first, 1 of 1)

- [Comparing YOLOv8 and Mask R-CNN for instance segmentation in complex orchard environments](https://mlsanity.com/paper/2312.07935/) (2023)

## Abstract (arXiv)

Fruit size and leaf area are important indicators for plant health and are of interest for plant nutrient management, plant protection and harvest. In this research, an image-based method for measuring the fruit volume as well as the leaf area for cabbage is presented. For this purpose, a mask region-based convolutional neural network (Mask R-CNN) was trained to segment the cabbage fruit from the leaves and assign it to the corresponding plant. The results indicated that even with a single camera, the developed method can provide a calculation accuracy of fruit size of 92.6% and an accuracy of leaf area of 89.8% on individual plant level.