gptkbp:instance_of
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gptkb:Transformers
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gptkbp:application
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Image Classification
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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:attention_mechanism
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Multi-head Attention
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gptkbp:coat_of_arms
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gptkb:32
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gptkbp:collaborator
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Various Universities
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gptkbp:community_support
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Active
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gptkbp:computational_cost
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gptkb:High
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gptkbp:contribution
|
Advancement of Vision Transformers
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gptkbp:developed_by
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gptkb:Google_Research
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gptkbp:drops
|
0.1
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gptkbp:economic_impact
|
gptkb:Significant
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gptkbp:evaluates
|
F1 Score
|
gptkbp:feature_extractor
|
gptkb:Yes
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gptkbp:field_of_study
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gptkb:Computer_Vision
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gptkbp:future_prospects
|
Ongoing
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gptkbp:gpu
|
gptkb:Yes
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gptkbp:has_publications
|
Vision Transformers for Image Recognition
|
https://www.w3.org/2000/01/rdf-schema#label
|
Vi T-H
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gptkbp:hyperparameters
|
Tunable
|
gptkbp:influenced_by
|
gptkb:BERT
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gptkbp:initiated_by
|
Ge LU
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gptkbp:input_output
|
224x224
|
gptkbp:invention
|
gptkb:None
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gptkbp:is_a_framework_for
|
gptkb:Tensor_Flow
gptkb:Py_Torch
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gptkbp:is_cited_in
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gptkb:High
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gptkbp:is_open_source
|
gptkb:Yes
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gptkbp:is_optimized_for
|
gptkb:Adam
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gptkbp:is_taught_in
|
0.001
|
gptkbp:is_trained_in
|
gptkb:Image_Net
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gptkbp:losses
|
Cross-entropy Loss
|
gptkbp:migration
|
Supported
|
gptkbp:model
|
Large
Vi T-B, Vi T-L
|
gptkbp:num_parameters
|
632 million
|
gptkbp:orbital_period
|
over 600 million
|
gptkbp:output_activation
|
Softmax
|
gptkbp:performance
|
Available
Top-1 Accuracy
|
gptkbp:provides_information_on
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gptkb:CIFAR-10
gptkb:Yes
|
gptkbp:related_to
|
gptkb:Deep_Learning
|
gptkbp:resolution
|
1000 classes
|
gptkbp:sister_channel
|
gptkb:3
|
gptkbp:successor
|
Vi T-G
|
gptkbp:training
|
Days
Self-supervised Learning
|
gptkbp:tuning
|
Possible
|
gptkbp:user_base
|
Researchers, Developers
|
gptkbp:uses
|
Self-Attention Mechanism
|
gptkbp:uses_attention
|
gptkb:Yes
|
gptkbp:uses_patch_embedding
|
gptkb:Yes
|
gptkbp:uses_positional_encoding
|
gptkb:Yes
|
gptkbp:year_established
|
gptkb:2021
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gptkbp:bfsParent
|
gptkb:Transformers
|
gptkbp:bfsLayer
|
4
|