Siamese Neural Networks for One-Shot Image Recognition

@inproceedings{Koch2015SiameseNN,
  title={Siamese Neural Networks for One-Shot Image Recognition},
  author={Gregory Koch},
  year={2015}
}
  • Gregory Koch
  • Published 2015
The process of learning good features for machine learning applications can be very computationally expensive and may prove difficult in cases where little data is available. A prototypical example of this is the one-shot learning setting, in which we must correctly make predictions given only a single example of each new class. In this paper, we explore a method for learning siamese neural networks which employ a unique structure to naturally rank similarity between inputs. Once a network has… CONTINUE READING
Highly Influential
This paper has highly influenced 26 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 329 citations. REVIEW CITATIONS
242 Citations
24 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 242 extracted citations

329 Citations

0100200201620172018
Citations per Year
Semantic Scholar estimates that this publication has 329 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 24 references

A survey on metric learning for feature vectors and structured data

  • Yoshua Bengio
  • arXiv preprint arXiv : 1306 . 6709
  • 2013

Towards an empirical foundation for assessing bayesian optimization of hyperparam - eters

  • Li Fe-Fei, Robert Fergus, Pietro Perona
  • NIPS workshop on Bayesian Optimization in Theory…
  • 2013

Similar Papers

Loading similar papers…