| Technical Name | Development of fruit tree industry monitoring technology based on multi-source image recognition technology | ||
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| Project Operator | Taiwan Agricultural Research Institute Council of Agriculture, Executive Yuan | ||
| Project Host | 郭鴻裕, 陳淑佩, 林毓雯, 周呈霙, 王驥魁 | ||
| Summary | Integrating deep learning, 3D information analysis, hyperspectral analysis, computer vision analysiscombined the multi-source images to develop fruit quality monitoring techniques, including: planting area monitoring, position monitoring, yield monitoring, harvesting time prediction, fruit maturity measurement, fruit quality testing, to achieve the goal of enhancing industrial value. |
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| Scientific Breakthrough | Identification system applied to fruit trees classification can reach mean average precision of 0.85. Airborne LiDAR can penetrate the screen-house to obtain the fruit trees information inside. Monitoring the production seasonrelease yield prediction monthly. Automatic fruit selection reduces human’s screening,we use hyperspectral technology to measure fruit maturity. |
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| Industrial Applicability | AgricultureFood Agency: Interpret fruit treescalculate area. BAPHIQ: Apply height data for Tessaratoma papillosa Drury. Agribusiness: Farm monitoring. Council of Agriculture: Keep yieldprice in balance by yield prediction. Industry: We cooperated with Farmer’s Associationtwo companies for automatic fruit selectionautomatic interpretation of fruit maturity. |
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| Keyword | Fruit Tree Identification Image Segmentation Machine Learning Convolutional Neural Network Airborne LiDAR Hyperspectral Analysis Yield Predict Quality Inspection Land Usage Agricultural Monitering | ||
| Notes | |||
- Contact
- hj@tari.gov.tw
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