Crop Guidance Photography Algorithm for Mobile Terminals
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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-02-01
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| Series: | Agriculture |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-0472/14/2/271 |
| _version_ | 1797299196334702592 |
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| author | Yunsong Jia Qingxin Zhao Yi Xiong Xin Chen Xiang Li |
| author_facet | Yunsong Jia Qingxin Zhao Yi Xiong Xin Chen Xiang Li |
| author_sort | Yunsong Jia |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-07T22:47:09Z |
| format | Article |
| id | doaj.art-fe8702cd5b034afc9ad66565d01bb15d |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-07T22:47:09Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj.art-fe8702cd5b034afc9ad66565d01bb15d2024-02-23T15:03:46ZengMDPI AGAgriculture2077-04722024-02-0114227110.3390/agriculture14020271Crop Guidance Photography Algorithm for Mobile TerminalsYunsong Jia0Qingxin Zhao1Yi Xiong2Xin Chen3Xiang Li4College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, ChinaCollege of Information and Electrical Engineering, China Agricultural University, Beijing 100083, ChinaCollege of Information and Electrical Engineering, China Agricultural University, Beijing 100083, ChinaCollege of Information and Electrical Engineering, China Agricultural University, Beijing 100083, ChinaCollege of Information and Electrical Engineering, China Agricultural University, Beijing 100083, ChinaThe 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.https://www.mdpi.com/2077-0472/14/2/271guidance promptslightweightmobilenet modelorientation detection |
| spellingShingle | Yunsong Jia Qingxin Zhao Yi Xiong Xin Chen Xiang Li Crop Guidance Photography Algorithm for Mobile Terminals Agriculture guidance prompts lightweight mobilenet model orientation detection |
| title | Crop Guidance Photography Algorithm for Mobile Terminals |
| title_full | Crop Guidance Photography Algorithm for Mobile Terminals |
| title_fullStr | Crop Guidance Photography Algorithm for Mobile Terminals |
| title_full_unstemmed | Crop Guidance Photography Algorithm for Mobile Terminals |
| title_short | Crop Guidance Photography Algorithm for Mobile Terminals |
| title_sort | crop guidance photography algorithm for mobile terminals |
| topic | guidance prompts lightweight mobilenet model orientation detection |
| url | https://www.mdpi.com/2077-0472/14/2/271 |
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