| Technical Name | Extreme small object identification for UAV monitoring | ||
|---|---|---|---|
| Project Operator | National Taiwan Ocean University | ||
| Project Host | 謝君偉 | ||
| Summary | We develop the new neural network architecture to improve execution speedaccuracy. The result shows that our AI detection system can run on a microcomputer in real-time, meanwhile its accuracy 90. We put that microcomputer on a dronereturn the result to smartphone App in real-time. | ||
| Market Potential Analysis | 可應用於各縣市的警察局及交通大隊、降低人力成本。 | ||
| Industrial Applicability | We develop the new neural network architecture to improve execution speedaccuracy. The result shows that our AI detection system can run on a microcomputer in real-time, meanwhile its accuracy 90. We put that microcomputer on a dronereturn the result to smartphone App in real-time. | ||
| Keyword | Deep Learning Extreme small object identification UAV monitoring Low-power design AI detection system embedded system quality agriculture car flow detection pest detection human flow detection Low-power | ||
| Notes | |||
- Contact
- irenelo@ntou.edu.tw
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