One-shot learning

One-shot learning is an object categorization problem of current research interest in computer vision. Whereas most machine learning based object… (More)
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Topic mentions per year

Topic mentions per year

2006-2018
02420062018

Papers overview

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2017
2017
One-shot learning is a challenging problem where the aim is to recognize a class identified by a single training image. Given the… (More)
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2016
2016
One-shot learning is usually tackled by using generative models or discriminative embeddings. Discriminative methods based on… (More)
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2016
2016
One of the key challenges in applying reinforcement learning to complex robotic control tasks is the need to gather large amounts… (More)
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2016
2016
This paper presents a method for one-shot learning of dexterous grasps, and grasp generation for novel objects. A model of each… (More)
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Highly Cited
2015
Highly Cited
2015
Siamese Neural Networks for One-Shot Image Recognition Gregory Koch Master of Science Graduate Department of Computer Science… (More)
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2014
2014
One-shot learning – the human ability to learn a new concept from just one or a few examples – poses a challenge to traditional… (More)
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Highly Cited
2013
Highly Cited
2013
People can learn a new visual class from just one example, yet machine learning algorithms typically require hundreds or… (More)
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2013
2013
We model a “one-shot learning” situation, where very few observations y1, ..., yn ∈ R are available. Associated with each… (More)
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2012
2012
In this work, a one-shot learning solution to the t-maze road sign problem is presented. This problem consists in taking the… (More)
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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… (More)
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