Meet the authors: Hanchuan Peng, Peng Xie, and Feng Xiong
In a recent paper at , Hanchuan Peng, Peng Xie, and Feng Xiong from Southeast University describe a deep learning method to characterize complete single-neuron morphologies, which can discover neuron projection patterns of diverse cells and learn neuronal morphology representation. In this interview...
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Veröffentlicht in: | Patterns (New York, N.Y.) N.Y.), 2024-01, Vol.5 (1), p.100912, Article 100912 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | In a recent paper at
, Hanchuan Peng, Peng Xie, and Feng Xiong from Southeast University describe a deep learning method to characterize complete single-neuron morphologies, which can discover neuron projection patterns of diverse cells and learn neuronal morphology representation. In this interview, the authors shared the story behind the paper and their research experience. This interview is a companion to these authors' recent paper, "DSM: Deep sequential model for complete neuronal morphology representation and feature extraction."
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ISSN: | 2666-3899 2666-3899 |
DOI: | 10.1016/j.patter.2023.100912 |