Crop Guidance Photography Algorithm for Mobile Terminals

Yunsong Jia, Qingxin Zhao, Yi Xiong, Xin Chen and Xiang Li ()
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Yunsong Jia: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Qingxin Zhao: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Yi Xiong: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Xin Chen: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
Xiang Li: College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China

Agriculture, 2024, vol. 14, issue 2, 1-21

Abstract: The issues of inadequate digital proficiency among agricultural practitioners and the suboptimal image quality captured using mobile smart devices have been addressed by providing appropriate guidance to photographers to properly position their mobile devices during image capture. An application for crop guidance photography was developed, which involved classifying and identifying crops from various orientations and providing guidance prompts. Three steps were executed, including increasing sample randomness, model pruning, and knowledge distillation, to improve the MobileNet model for constructing a smartphone-based orientation detection model with high accuracy and low computational requirements. Subsequently, the application was realized by utilizing the classification results for guidance prompts. The test demonstrated that this method effectively and seamlessly guided agricultural practitioners in capturing high-quality crop images, providing effective photographic guidance for farmers.

Keywords: guidance prompts; lightweight; mobilenet model; orientation detection (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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