Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

One-shot learning

One-shot learning is an object categorization problem of current research interest in computer vision. Whereas most machine learning based object… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2017
Highly Cited
2017
This paper tackles the task of semi-supervised video object segmentation, i.e., the separation of an object from the background… Expand
  • figure 2
  • figure 3
  • figure 4
  • table 1
  • table 2
Highly Cited
2017
Highly Cited
2017
Recent advances in one-shot learning have produced models that can learn from a handful of labeled examples, for passive… Expand
  • figure 1
  • figure 2
  • figure 3
  • table 1
Highly Cited
2017
Highly Cited
2017
Low-shot learning methods for image classification support learning from sparse data. We extend these techniques to support dense… Expand
  • figure 1
  • figure 2
  • table 1
  • figure 3
  • table 2
Highly Cited
2016
Highly Cited
2016
Learning from a few examples remains a key challenge in machine learning. Despite recent advances in important domains such as… Expand
  • figure 1
  • table 1
  • figure 2
  • table 2
  • table 3
Highly Cited
2016
Highly Cited
2016
Despite recent breakthroughs in the applications of deep neural networks, one setting that presents a persistent challenge is… Expand
  • figure 1
  • figure 2
  • table 1
  • figure 3
  • figure 4
Highly Cited
2016
Highly Cited
2016
One-shot learning is usually tackled by using generative models or discriminative embeddings. Discriminative methods based on… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • table 1
Highly Cited
2015
Highly Cited
2015
The process of learning good features for machine learning applications can be very computationally expensive and may prove… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
2015
2015
  • A. Wong, A. Yuille
  • IEEE International Conference on Computer Vision…
  • 2015
  • Corpus ID: 13468902
The task of discriminating one object from another is almost trivial for a human being. However, this task is computationally… Expand
Highly Cited
2006
Highly Cited
2006
Learning visual models of object categories notoriously requires hundreds or thousands of training examples. We show that it is… Expand
Highly Cited
2003
Highly Cited
2003
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and… Expand
  • figure 1
  • figure 2
  • figure 3
  • table 1
  • figure 4