Statements (63)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:microprocessor
|
| gptkbp:bfsLayer |
5
|
| gptkbp:bfsParent |
gptkb:Few-Shot_Learning
gptkb:one-shot_learning |
| gptkbp:adapted_into |
multi-modal learning
|
| gptkbp:analyzes |
t-SNE
|
| gptkbp:applies_to |
natural language processing
biometric identification |
| gptkbp:consists_of |
two identical subnetworks
|
| gptkbp:controls |
variable input sizes
|
| gptkbp:developed_by |
gptkb:one-shot_learning
|
| gptkbp:first_introduced |
Bromley et al.
|
| https://www.w3.org/2000/01/rdf-schema#label |
Siamese networks
|
| gptkbp:input_output |
similarity score
|
| gptkbp:is_compared_to |
two input samples
|
| gptkbp:is_designed_to |
learn embeddings
|
| gptkbp:is_effective_against |
few-shot learning
|
| gptkbp:is_evaluated_by |
accuracy metrics
|
| gptkbp:is_implemented_in |
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch convolutional layers recurrent layers |
| gptkbp:is_popular_in |
computer vision
|
| gptkbp:is_related_to |
twin networks
|
| gptkbp:is_used_for |
gptkb:musician
gptkb:robot language translation augmented reality data visualization question answering time series analysis data mining predictive modeling sentiment analysis customer segmentation data augmentation data compression fraud detection self-driving cars social network analysis data clustering spam detection feature extraction anomaly detection chatbot development knowledge discovery text classification detect anomalies text similarity game AI image similarity match pairs of data metric learning video similarity |
| gptkbp:is_used_in |
recommendation systems
medical image analysis |
| gptkbp:training |
labeled datasets
contrastive loss triplet loss |
| gptkbp:tuning |
transfer learning
|
| gptkbp:used_in |
image recognition
signature verification face verification |