Spectroscopy and Spectral Analysis, Volume. 42, Issue 2, 609(2022)
A Combination of Multiple Deep Learning Methods Applied to Small-Sample Space Objects Classification
References(9)
[1] Cho S, Kim K J[D]. Pattern Analysis & Applications, 553(2015).
[3] Mohiuddin A, Raihan S, Syed M S I[D]. Electronics, 9, 1295(2020).
[4] et al[D]. Science, 344, 1492(2014).
[5] Kristian S, Rudolf S[D]. Advances in Data Analysis and Classification, 15, 83(2020).
[7] Cortes C, Ghahramani Z, Welling M[D]. NIPS, 2672(2014).
[8] She Q, Wang Z, Ward T E[D]. Generative Adversarial Networks: A Sarvey and Taxonomy(2019).
[9] Koziarski M, Krawczyk B, Wozniak M[D]. Neurocomputing, 19(2019).
[10] Bengio Y, Bottou L, LeCun Y et al[C]. Proceedings of the IEEE, 2278(1998).
[11] Luo A L, Qiu B, Zheng Z P et al[D]. Publications of the Astronomical Society of the Pacific, 132, 024504(2020).
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Shi-yu DENG, Cheng-zhi LIU, Yong TAN, De-long LIU, Nan ZHANG, Zhe KANG, Zhen-wei LI, Cun-bo FAN, Chun-xu JIANG, Zhong LÜ. A Combination of Multiple Deep Learning Methods Applied to Small-Sample Space Objects Classification[J]. Spectroscopy and Spectral Analysis, 2022, 42(2): 609
Paper Information
Category: Research Articles
Received: Jan. 8, 2021
Accepted: Feb. 7, 2021
Published Online: Apr. 2, 2022
The Author Email: Shi-yu DENG (dengsy@cho.ac.cn)
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