Vi T-B

GPTKB entity

Statements (66)
Predicate Object
gptkbp:instance_of gptkb:Transformers_character
gptkbp:bfsLayer 4
gptkbp:bfsParent gptkb:Transformers_character
gptkbp:application Medical imaging
Autonomous driving
Facial recognition
Video analysis
Image generation
Image classification
Object detection
Semantic segmentation
gptkbp:architectural_style gptkb:Transformers_character
gptkbp:cache_size gptkb:32
gptkbp:developed_by gptkb:Google_Research
gptkbp:established Ge LU
gptkbp:features Data augmentation
Fine-tuning
self-attention mechanism
positional encoding
Global average pooling
Gradient clipping
Attention maps
Class token
Image normalization
Interpretability tools
Layer-wise learning rate decay
Model ensembling
Patch size 16x16
Transferable features
patch embeddings
gptkbp:first_introduced Xavier initialization
gptkbp:game_components Layer normalization
Multi-head attention
Residual connections
Feed-forward network
gptkbp:has_website Computer vision
https://www.w3.org/2000/01/rdf-schema#label Vi T-B
gptkbp:influenced_by gptkb:Attention_is_All_You_Need
gptkbp:input_output 224x224
gptkbp:is_evaluated_by gptkb:CIFAR-10
gptkb:Stanford_Dogs
gptkb:CIFAR-100
F1 score
Oxford Pets
gptkbp:losses Cross-entropy loss
gptkbp:orbital_period 86 million
gptkbp:performance Top-1 accuracy
88.55%
gptkbp:predecessor CN Ns
gptkbp:provides_information_on gptkb:Image_Net
1.2 million images
gptkbp:reduces 0.1
gptkbp:related_to Deep learning
Neural networks
gptkbp:release_year gptkb:2020
gptkbp:resolution 1000 classes
224x224 pixels
gptkbp:successor gptkb:Vi_T-L
gptkbp:training gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
0.001
Supervised learning
gptkbp:tuning gptkb:Adam_optimizer
gptkbp:uses Transfer learning
Self-Attention Mechanism
gptkbp:values 86 million