Effectively detecting anomalous diffusion via deep learning

被引：0
|
作者：
Pacheco-Pozo, Adrian [1 ,2 ]
Krapf, Diego [1 ,2 ]
机构：
[1] Colorado State Univ, Dept Elect & Comp Engn, Ft Collins, CO 80523 USA
[2] Colorado State Univ, Sch Biomed Engn, Ft Collins, CO 80523 USA
来源：
NATURE COMPUTATIONAL SCIENCE | 2024年 / 4卷 / 10期
关键词：
10;
D O I：
10.1038/s43588-024-00705-5
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
A deep learning algorithm is presented to classify single-particle tracking trajectories into theoretical models of anomalous diffusion and detect if the trajectory is related to a model not originally found within the training dataset.
引用
收藏
页码：731 / 732
页数：2
相关论文
共 50 条
  • [21] A Learning Method of Detecting Anomalous Pedestrian
    Liu, Yue
    Zhang, Jun
    Liu, Zhijing
    ADVANCED DATA MINING AND APPLICATIONS, PROCEEDINGS, 2008, 5139 : 604 - +
  • [22] Reliable deep learning in anomalous diffusion against out-of-distribution dynamics
    Feng, Xiaochen
    Sha, Hao
    Zhang, Yongbing
    Su, Yaoquan
    Liu, Shuai
    Jiang, Yuan
    Hou, Shangguo
    Han, Sanyang
    Ji, Xiangyang
    NATURE COMPUTATIONAL SCIENCE, 2024, 4 (10): : 761 - 772
  • [23] Reliable deep learning in anomalous diffusion against out-of-distribution dynamics
    Feng, Xiaochen
    Sha, Hao
    Zhang, Yongbing
    Su, Yaoquan
    Liu, Shuai
    Jiang, Yuan
    Hou, Shangguo
    Han, Sanyang
    Ji, Xiangyang
    NATURE COMPUTATIONAL SCIENCE, 2024, 4 (11): : 877 - 877
  • [24] Author Correction: Bayesian deep learning for error estimation in the analysis of anomalous diffusion
    Henrik Seckler
    Ralf Metzler
    Nature Communications, 14
  • [25] Detecting anomalous proteins using deep representations
    Michael-Pitschaze, Tomer
    Cohen, Niv
    Ofer, Dan
    Hoshen, Yedid
    Linial, Michal
    NAR GENOMICS AND BIOINFORMATICS, 2024, 6 (01)
  • [26] Detecting Duplicate Questions in Stack Overflow via Deep Learning Approaches
    Wang, Liting
    Zhang, Li
    Jiang, Jing
    2019 26TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC), 2019, : 506 - 513
  • [27] A Deep Learning Approach for Detecting Colorectal Cancer via Raman Spectra
    Cao, Zheng
    Pan, Xiang
    Yu, Hongyun
    Hua, Shiyuan
    Wang, Da
    Chen, Danny Z.
    Zhou, Min
    Wu, Jian
    BME FRONTIERS, 2022, 2022
  • [28] Detecting Object and Direction for Polar Electronic Components via Deep Learning
    Chen W.-S.
    Ren Z.-G.
    Wu Z.-Z.
    Fu M.-Y.
    Zidonghua Xuebao/Acta Automatica Sinica, 2021, 47 (07): : 1701 - 1709
  • [29] Detecting Compiler Bugs Via a Deep Learning-Based Framework
    Tang, Yixuan
    Ren, Zhilei
    Jiang, He
    Qiao, Lei
    Liu, Dong
    Zhou, Zhide
    Kong, Weiqiang
    INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, 2022, 32 (05) : 661 - 691
  • [30] Detecting Trees in Street Images via Deep Learning With Attention Module
    Xie, Qian
    Li, Dawei
    Yu, Zhenghao
    Zhou, Jun
    Wang, Jun
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 69 (08) : 5395 - 5406
12345