Empowering novel scholarship at the intersection of machine learning/deep learning and ecology

被引:6
|
作者
Dutta, Malay Kishore [1 ]
Arhonditsis, George [2 ]
机构
[1] Amity Univ, Amity Ctr Artificial Intelligence, Noida, India
[2] Univ Toronto Scarborough, Dept Phys & Environm Sci, Ecol Modelling Lab, Toronto, ON, Canada
关键词
Ecological informatics; Deep-learning; Machine-learning; Ecological modelling;
D O I
10.1016/j.ecoinf.2023.102249
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
引用
收藏
页数:2
相关论文
共 50 条
  • [31] Learning in the machine: The symmetries of the deep learning channel
    Baldi, Pierre
    Sadowski, Peter
    Lu, Zhiqin
    NEURAL NETWORKS, 2017, 95 : 110 - 133
  • [32] A Review of Machine Learning and Deep Learning Applications
    Shinde, Pramila P.
    Shah, Seema
    2018 FOURTH INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION CONTROL AND AUTOMATION (ICCUBEA), 2018,
  • [33] Machine learning after the deep learning revolution
    Wray Buntine
    Frontiers of Computer Science, 2020, 14
  • [34] Visual inspection by deep learning and machine learning
    Nagata T.
    Hashimoto D.
    Journal of Japan Institute of Electronics Packaging, 2020, 23 (04) : 271 - 274
  • [35] Machine learning and deep learning applied in ultrasound
    Pehrson, Lea Marie
    Lauridsen, Carsten
    Nielsen, Michael Bachmann
    ULTRASCHALL IN DER MEDIZIN, 2018, 39 (04): : 379 - 381
  • [36] Machine Learning and Deep Learning Methods for Cybersecurity
    Xin, Yang
    Kong, Lingshuang
    Liu, Zhi
    Chen, Yuling
    Li, Yanmiao
    Zhu, Hongliang
    Gao, Mingcheng
    Hou, Haixia
    Wang, Chunhua
    IEEE ACCESS, 2018, 6 : 35365 - 35381
  • [37] How deep learning is empowering semantic segmentationTraditional and deep learning techniques for semantic segmentation: A comparison
    Uroosa Sehar
    Muhammad Luqman Naseem
    Multimedia Tools and Applications, 2022, 81 : 30519 - 30544
  • [38] Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains (Demo)
    Lan, Yixiao
    Liu, Yuan
    Li, Boyang
    Miao, Chunyan
    THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 2021, 35 : 16063 - 16066
  • [39] Deep learning as a tool for ecology and evolution
    Borowiec, Marek L.
    Dikow, Rebecca B.
    Frandsen, Paul B.
    McKeeken, Alexander
    Valentini, Gabriele
    White, Alexander E.
    METHODS IN ECOLOGY AND EVOLUTION, 2022, 13 (08): : 1640 - 1660
  • [40] Deep Tobit networks: A novel machine learning approach to microeconometrics
    Zhang, Jiaming
    Li, Zhanfeng
    Song, Xinyuan
    Ning, Hanwen
    NEURAL NETWORKS, 2021, 144 : 279 - 296