Framework for Apple Phenotype Feature Extraction Using Instance Segmentation and Edge Attention Mechanism

A method for apple phenotypic feature extraction and growth anomaly identification based on deep learning and natural language processing technologies is proposed in this paper, aiming to enhance the accuracy of apple quality detection and anomaly prediction in agricultural production. This method i...

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Veröffentlicht in:	Agriculture (Basel) Jg. 15; H. 3; S. 305
Hauptverfasser:	Wang, Zichong, Cui, Weiyuan, Huang, Chenjia, Zhou, Yuhao, Zhao, Zihan, Yue, Yuchen, Dong, Xinrui, Lv, Chunli
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.02.2025
Schlagworte:	Accuracy agricultural economic analysis Agricultural production Agriculture Anomalies apple phenotype feature extraction Apples Automation Classification Computational linguistics Computer vision Data analysis Data integration Decision support systems Deep learning Dimensional analysis Economic analysis Entropy Feature extraction Fruits Genotype & phenotype growth anomaly recognition Image processing Image quality Image segmentation Instance segmentation Language processing Localization Machine learning Meteorological data Methods Natural language interfaces Natural language processing Neural networks Perception Phenotypes Predictions Quality management Recall Semantics China Germany
ISSN:	2077-0472, 2077-0472
Online-Zugang:	Volltext
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