[HTML][HTML] Comprehensive review on 3D point cloud segmentation in plants

H Song, W Wen, S Wu, X Guo - Artificial Intelligence in Agriculture, 2025 - Elsevier
Segmentation of three-dimensional (3D) point clouds is fundamental in comprehending
unstructured structural and morphological data. It plays a critical role in research related to …

Maize stem–leaf segmentation framework based on deformable point clouds

X Yang, T Miao, X Tian, D Wang, J Zhao, L Lin… - ISPRS Journal of …, 2024 - Elsevier
The efficacy of three-dimensional (3D) point clouds in studying crop morphological
structures is based on their direct and accurate data presentation ability. With deep-learning …

3D reconstruction and characterization of cotton bolls in situ based on UVA technology

S ** with organ-level instance segmentation from point cloud
L Jiang, C Li, L Fu - Computers and Electronics in Agriculture, 2025 - Elsevier
Abstract Three-dimensional (3D) plant phenoty** techniques measure organ-level traits
effectively and provide detailed plant growth information to breeders. In apple tree breeding …

Estimation of cotton boll number and main stem length based on 3D gaussian splatting

L Jiang, C Li, J Sun, P Chee, L Fu - 2024 ASABE Annual …, 2024 - elibrary.asabe.org
Cotton is an important economic crop widely grown worldwide to produce textiles. Breeding
programs aim to select genotypes with desirable architectural traits to develop new varieties …

Research on visualization of cotton canopy structure and extraction of feature parameters based on dual-perspective point cloud data

Y Hu, S Wen, L Zhang, Y Lan… - International Journal of …, 2024 - Taylor & Francis
Cotton is one of the crops that requires the most time and labor. Precision agriculture
technology is required for efficient management of cotton, and the identification of cotton …

[HTML][HTML] Using high-throughput phenotype platform MVS-Pheno to reconstruct the 3D morphological structure of wheat

W Li, S Wu, W Wen, X Lu, H Liu, M Zhang, P **ao… - AoB Plants, 2024 - ncbi.nlm.nih.gov
It is of great significance to study the plant morphological structure for improving crop yield
and achieving efficient use of resources. Three dimensional (3D) information can more …

[HTML][HTML] 3D neural architecture search to optimize segmentation of plant parts

F Saeed, C Tan, T Liu, C Li - Smart Agricultural Technology, 2025 - Elsevier
Accurately segmenting plant parts from imagery is vital for improving crop phenotypic traits.
However, current 3D deep learning models for segmentation in point cloud data require …

[HTML][HTML] Automated Phenotypic Analysis of Mature Soybean Using Multi-View Stereo 3D Reconstruction and Point Cloud Segmentation

D Cui, P Liu, Y Liu, Z Zhao, J Feng - Agriculture, 2025 - mdpi.com
Phenotypic analysis of mature soybeans is a critical aspect of soybean breeding. However,
manually obtaining phenotypic parameters not only is time-consuming and labor intensive …

[HTML][HTML] A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model

K Yang, X Sun, R Li, Z He, X Wang, C Wang, B Wang… - Agronomy, 2025 - mdpi.com
Quantifying planting layouts during the seedling stage of mung beans (Vigna radiata L.) is
crucial for assessing cultivation conditions and providing support for precise management …