Vision Transformers

GPTKB entity

Statements (65)
Predicate Object
gptkbp:instance_of gptkb:neural_networks
gptkbp:applies_to gptkb:Computer_Vision
gptkbp:based_on gptkb:Transformer_Architecture
gptkbp:challenges Memory Usage
Training Time
Computational Cost
gptkbp:competes_with gptkb:neural_networks
gptkbp:designed_for Image Classification
gptkbp:developed_by gptkb:Google_Research
gptkbp:enhances Feature Extraction
gptkbp:has_achieved State-of-the-art Performance
Image Recognition Tasks
gptkbp:has_variants gptkb:Dei_T
gptkb:Swin_Transformer
gptkb:Vi_T
https://www.w3.org/2000/01/rdf-schema#label Vision Transformers
gptkbp:introduced_in gptkb:2020
gptkbp:is_adopted_by gptkb:Industry
Academia
gptkbp:is_applied_in Computer Vision Tasks
gptkbp:is_compared_to gptkb:neural_networks
gptkbp:is_effective_against Multi-Task Learning
gptkbp:is_evaluated_by gptkb:mobile_devices
gptkb:Edge_Computing
gptkb:cloud_computing
gptkb:CIFAR-10_Dataset
gptkb:COCO_Dataset
gptkb:Image_Net_Dataset
Real-Time Applications
gptkbp:is_explored_in gptkb:Few-Shot_Learning
gptkb:Zero-Shot_Learning
Explainability
Model Compression
Adversarial Robustness
gptkbp:is_influenced_by gptkb:Deep_Learning
Attention Mechanism
gptkbp:is_integrated_with Ensemble Methods
Hybrid Models
Other AI Models
gptkbp:is_popular_in gptkb:scientific_community
gptkbp:is_promoted_by Online Courses
Research Institutions
Tech Companies
gptkbp:is_related_to gptkb:Natural_Language_Processing
gptkb:machine_learning
Generative Models
gptkbp:is_scalable High-Resolution Images
gptkbp:is_supported_by Conferences
Research Papers
Open Source Frameworks
Pretrained Models
gptkbp:is_trained_in Limited Labeled Data
gptkbp:is_used_in gptkb:Autonomous_Vehicles
Facial Recognition
Medical Imaging
gptkbp:performance gptkb:stage_adaptation
gptkbp:requires Large Datasets
gptkbp:used_for Image Classification
gptkbp:uses Self-Attention Mechanism
gptkbp:utilizes Self-Attention Mechanism
Patch Embedding
gptkbp:bfsParent gptkb:GLUE_benchmark
gptkb:CLIP
gptkb:Swin_Transformer
gptkbp:bfsLayer 5