Automatic recognition method of wheat lodging image based on ACSNet

Hecang Zang; Linyuan Ru; Qiaoli Zhao; Qing Zhao; Guoqing Zheng; Guoqiang Li

doi:10.1117/12.3011438

8 November 2023 Automatic recognition method of wheat lodging image based on ACSNet

Hecang Zang, Linyuan Ru, Qiaoli Zhao, Qing Zhao, Guoqing Zheng, Guoqiang Li

Proceedings Volume 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023); 129231P (2023) https://doi.org/10.1117/12.3011438
Event: 3rd International Conference on Artificial Intelligence, Virtual Reality and Visualization (AIVRV 2023), 2023, Chongqing, China

Abstract

Lodging is a key factor, which affect yield and quality of wheat. Timely and accurate acquisition of wheat lodging information is conducive to lodging identification and breeding of improved varieties. In this study, based on the UAV visible light image obtained during the wheat filling period, the wheat lodging image data set was constructed, and the ACSNet network model was selected as the main model of segmentation task. The model can effectively extract local context information features. The result show that the prediction accuracy of ACSNet model was 87.5 %, which could accurately and efficiently complete the automatic classification of wheat lodging. It had high accuracy and applicability, and provided an important basis for agricultural insurance companies to identify wheat lodging and determine agricultural losses.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hecang Zang, Linyuan Ru, Qiaoli Zhao, Qing Zhao, Guoqing Zheng, and Guoqiang Li "Automatic recognition method of wheat lodging image based on ACSNet", Proc. SPIE 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023), 129231P (8 November 2023); https://doi.org/10.1117/12.3011438

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