Advanced search
1 file | 5.33 MB Add to list

Improved deep embedding learning based on stochastic symmetric triplet loss and local sampling

Bac Nguyen Cong (UGent) and Bernard De Baets (UGent)
(2020) Neurocomputing. 402. p.209-219
Author
Organization
Keywords
Cognitive Neuroscience, Artificial Intelligence, Computer Science Applications

Downloads

  • KERMIT-A1-572.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 5.33 MB

Citation

Please use this url to cite or link to this publication:

MLA
Nguyen Cong, Bac, and Bernard De Baets. “Improved Deep Embedding Learning Based on Stochastic Symmetric Triplet Loss and Local Sampling.” Neurocomputing, vol. 402, 2020, pp. 209–19.
APA
Nguyen Cong, B., & De Baets, B. (2020). Improved deep embedding learning based on stochastic symmetric triplet loss and local sampling. Neurocomputing, 402, 209–219.
Chicago author-date
Nguyen Cong, Bac, and Bernard De Baets. 2020. “Improved Deep Embedding Learning Based on Stochastic Symmetric Triplet Loss and Local Sampling.” Neurocomputing 402: 209–19.
Chicago author-date (all authors)
Nguyen Cong, Bac, and Bernard De Baets. 2020. “Improved Deep Embedding Learning Based on Stochastic Symmetric Triplet Loss and Local Sampling.” Neurocomputing 402: 209–219.
Vancouver
1.
Nguyen Cong B, De Baets B. Improved deep embedding learning based on stochastic symmetric triplet loss and local sampling. Neurocomputing. 2020;402:209–19.
IEEE
[1]
B. Nguyen Cong and B. De Baets, “Improved deep embedding learning based on stochastic symmetric triplet loss and local sampling,” Neurocomputing, vol. 402, pp. 209–219, 2020.
@article{8663208,
  author       = {Nguyen Cong, Bac and De Baets, Bernard},
  issn         = {0925-2312},
  journal      = {Neurocomputing},
  keywords     = {Cognitive Neuroscience,Artificial Intelligence,Computer Science Applications},
  language     = {eng},
  pages        = {209--219},
  title        = {Improved deep embedding learning based on stochastic symmetric triplet loss and local sampling},
  url          = {http://dx.doi.org/10.1016/j.neucom.2020.04.062},
  volume       = {402},
  year         = {2020},
}

Altmetric
View in Altmetric