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http://hdl.handle.net/10397/104440
| Title: | Meteorite detection and tracing with deep learning on FPGA platform | Authors: | Tseng, KK Lin, J Sun, H Yung, KL Ip, WH |
Issue Date: | 2019 | Source: | Advances in intelligent systems and computing, 2019, v. 834, p. 493-500 | Abstract: | At present, the strength of space exploration represents the strength of a country. Meteorite exploration is also part of the space field. The traditional meteorite detection and tracking technology are slow and not accurate. With the development of deep learning, computer detection technology becomes more and more accurate and efficient, which makes it possible to improve the accuracy and speed of meteorite detection. In this paper, the deep learning algorithm implemented by FPGA is applied to the meteorite detection, and the popular tracking algorithm is applied to the meteorite tracking, so that the structure of the meteorite detection and tracking system can meet the practical requirements. | Keywords: | Deep learning FPGA Meteorite detect Tracking |
Publisher: | Springer | Journal: | Advances in intelligent systems and computing | ISSN: | 2194-5357 | EISSN: | 2194-5365 | DOI: | 10.1007/978-981-13-5841-8_51 | Description: | Twelfth International Conference on Genetic and Evolutionary Computing, December 14-17, 2018, Changzhou, Jiangsu, China | Rights: | © Springer Nature Singapore Pte Ltd. 2019 This version of of the proceeding paper has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-981-13-5841-8_51. |
| Appears in Collections: | Conference Paper |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| Yung_Meteorite_Detection_Tracing.pdf | Pre-Published version | 994.29 kB | Adobe PDF | View/Open |
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