AIIC AI Intelligence Centre

SOURCE-LINKED INTELLIGENCE

MCLC-NET: Multimodal Continual Learning for Leaf Counting

arXiv · AI, language, vision and robotics · article · Sep 16, 2026 · UTC

Leaf counting is an important task in plant phenotyping for monitoring plant growth and estimating crop yield. Most existing methods rely on RGB images, but their performance is often affected by occlusion, lighting variations, and other real-world challenges. Additional modalities, such as depth and thermal images, can provide useful complementary information. However, multimodal leaf counting remains underexplored. Also, many existing methods assume that all training data are available simultaneously, which is impractical in real agricultural settings, where data is collected over time from

Read original source ↗ Open in workspace

recordType
paper
region
Global

Evidence & attribution

First collected: 2026-09-20T08:20:57.646Z. This is not the publication date.