| DOI | Resolve DOI: https://doi.org/10.1145/3546790.3546800 |
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| Author | Search for: Stewart, Terrence1; Search for: Drouin, Marc-Antoine1; Search for: Picard, Michel1; Search for: Djupkep Dizeu, Frank Billy1; Search for: Orth, Anthony1; Search for: Gagné, Guillaume |
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| Affiliation | - National Research Council of Canada. Digital Technologies
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| Format | Text, Article |
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| Conference | ICONS: International Conference on Neuromorphic Systems, July 27-29, 2022, Knoxville TN USA |
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| Physical description | 7 p. |
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| Abstract | In previous work, we prototyped a portable drone detection system using a DAVIS 346 event camera and a Raspberry Pi 4, running in 5.14 W. Here, we expand on this work by switching to the higher-resolution DVXplorer and by including a small neural network classifier system. The resulting system improves the range at which drones can be recognized (from 9m to 19m). We also demonstrate our novel in-lab test system, capable of generating controlled training data across a wide variety of lighting and optical conditions. The new 100-neuron classification system runs at 100Hz with an accuracy of 98% on our field test and 96% on the in-lab test suite. |
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| Publication date | 2022-07-27 |
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| Publisher | ACM |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 614d19e6-2611-4092-9a44-5dc0160f8334 |
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| Record created | 2022-10-05 |
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| Record modified | 2022-10-05 |
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