Statements (59)
Predicate | Object |
---|---|
gptkbp:instance_of |
gptkb:microprocessor
|
gptkbp:bfsLayer |
5
|
gptkbp:bfsParent |
gptkb:Few-Shot_Learning
|
gptkbp:applies_to |
image classification
|
gptkbp:based_on |
metric learning
similarity learning |
gptkbp:controls |
unseen classes
|
gptkbp:has_achievements |
state-of-the-art performance
|
https://www.w3.org/2000/01/rdf-schema#label |
Matching networks
|
gptkbp:improves |
sample efficiency
|
gptkbp:input_output |
similarity scores
|
gptkbp:inspired_by |
human learning
|
gptkbp:introduced |
Vinyals et al.
|
gptkbp:is_compared_to |
gptkb:Siamese_networks
transfer learning traditional supervised learning |
gptkbp:is_designed_for |
few-shot learning
|
gptkbp:is_evaluated_by |
gptkb:Stanford_Dogs_dataset
gptkb:Celeb_A_dataset gptkb:CIFAR-100_dataset MSCOCO dataset Oxford Pets dataset CUB-200-2011 dataset Caltech-101 dataset Fashion-MNIST dataset Omniglot dataset VGG Face dataset mini Image Net dataset |
gptkbp:is_implemented_in |
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch |
gptkbp:is_related_to |
meta-learning
|
gptkbp:is_used_for |
object detection
image retrieval semantic segmentation |
gptkbp:is_used_in |
gptkb:musician
gptkb:robot gptkb:computer gptkb:engine healthcare finance augmented reality computer vision natural language processing edge computing speech recognition sentiment analysis recommendation systems time series forecasting anomaly detection social media analysis text classification Io T applications game AI |
gptkbp:requires |
few training examples
support set |
gptkbp:training |
gradient descent
|
gptkbp:uses |
attention mechanism
|
gptkbp:utilizes |
prototypical networks
|
gptkbp:year_created |
gptkb:2016
|