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gptkbp:instance_of
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gptkb:Transformers
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gptkbp:application
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Medical imaging
Autonomous driving
Facial recognition
Video analysis
Image generation
Image classification
Object detection
Semantic segmentation
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gptkbp:architectural_style
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gptkb:Transformers
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gptkbp:architecture
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gptkb:Transformers
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gptkbp:batch_size
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gptkb:32
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gptkbp:components
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Layer normalization
Multi-head attention
Residual connections
Feed-forward network
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gptkbp:developed_by
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gptkb:Google_Research
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gptkbp:drops
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0.1
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gptkbp:evaluates
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gptkb:CIFAR-10
gptkb:Stanford_Dogs
gptkb:CIFAR-100
F1 score
Oxford Pets
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gptkbp:feature
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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
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gptkbp:has_website
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Computer vision
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https://www.w3.org/2000/01/rdf-schema#label
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Vi T-B
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gptkbp:influenced_by
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gptkb:Attention_is_All_You_Need
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gptkbp:initialization_method
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Xavier initialization
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gptkbp:initiated_by
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Ge LU
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gptkbp:input_output
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224x224
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gptkbp:is_taught_in
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0.001
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gptkbp:losses
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Cross-entropy loss
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gptkbp:num_parameters
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86 million
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gptkbp:orbital_period
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86 million
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gptkbp:performance
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Top-1 accuracy
88.55%
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gptkbp:predecessor
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CNNs
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gptkbp:provides_information_on
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gptkb:Image_Net
1.2 million images
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gptkbp:related_to
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Deep learning
Neural networks
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gptkbp:release_year
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gptkb:2020
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gptkbp:resolution
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1000 classes
224x224 pixels
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gptkbp:successor
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gptkb:Vi_T-L
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gptkbp:training
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Supervised learning
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gptkbp:training_programs
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gptkb:Tensor_Flow
gptkb:Py_Torch
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gptkbp:tuning
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gptkb:Adam_optimizer
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gptkbp:uses
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Transfer learning
Self-Attention Mechanism
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gptkbp:bfsParent
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gptkb:Transformers
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gptkbp:bfsLayer
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4
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