Meteorite Detection and Tracing with Deep Learning on FPGA Platform

0Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

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.

Cite

CITATION STYLE

APA

Tseng, K. K., Lin, J., Sun, H., Yung, K. L., & Ip, W. H. (2019). Meteorite Detection and Tracing with Deep Learning on FPGA Platform. In Advances in Intelligent Systems and Computing (Vol. 834, pp. 493–500). Springer Verlag. https://doi.org/10.1007/978-981-13-5841-8_51

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free