Agricultural Machinery Movement Trajectory Recognition Method Based on Two-Stage Joint Clustering

Agricultural Machinery Movement Trajectory Recognition Method Based on Two-Stage Joint Clustering

To address the challenges posed by the large scale of agricultural machinery trajectory data and the complexity of actual movement trajectories, this paper proposes a two-stage joint clustering method for agricultural machinery trajectory recognition to enhance accuracy and robustness. The first sta...

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Bibliographic Details
Main Authors: Shuya Zhang, Hui Liu, Xiangchen Cao, Zhijun Meng
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Agriculture
Subjects:
trajectory recognition
two-stage joint clustering
K-Means
Genetic Algorithm
DBSCAN
deep learning
Online Access:https://www.mdpi.com/2077-0472/14/12/2294
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