Meet the authors: Hanchuan Peng, Peng Xie, and Feng Xiong

IF 6.7 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Hanchuan Peng, Peng Xie, Feng Xiong
{"title":"Meet the authors: Hanchuan Peng, Peng Xie, and Feng Xiong","authors":"Hanchuan Peng, Peng Xie, Feng Xiong","doi":"10.1016/j.patter.2023.100912","DOIUrl":null,"url":null,"abstract":"<p>In a recent paper at <em>Patterns</em>, 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.</p><p>This interview is a companion to these authors’ recent paper, “DSM: Deep sequential model for complete neuronal morphology representation and feature extraction.”<span><sup>1</sup></span></p>","PeriodicalId":36242,"journal":{"name":"Patterns","volume":"27 1","pages":""},"PeriodicalIF":6.7000,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Patterns","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.patter.2023.100912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

In a recent paper at Patterns, 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.”1

认识作者彭汉川、谢鹏和熊峰
东南大学的彭汉川、谢鹏和熊峰最近在《Patterns》上发表论文,介绍了一种表征完整单神经元形态的深度学习方法,该方法可以发现不同细胞的神经元投射模式,并学习神经元形态表征。在这次访谈中,作者们分享了论文背后的故事和他们的研究经历。这次访谈是这些作者最近发表的论文《DSM:用于完整神经元形态表征和特征提取的深度序列模型 "1。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Patterns
Patterns Decision Sciences-Decision Sciences (all)
CiteScore
10.60
自引率
4.60%
发文量
153
审稿时长
19 weeks
期刊介绍:
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信