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gptkbp:instance_of
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gptkb:neural_networks
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gptkbp:architecture
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Image Classification
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gptkbp:base_model_of
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gptkb:Efficient_Net
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gptkbp:developed_by
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gptkb:Google_AI
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https://www.w3.org/2000/01/rdf-schema#label
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Efficient Net B0
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gptkbp:initiated_by
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Swish
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gptkbp:input_output
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224x224
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gptkbp:introduced_in
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gptkb:2019
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gptkbp:is_available_in
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gptkb:Tensor_Flow
gptkb:Keras
gptkb:Py_Torch
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gptkbp:is_cited_in
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Dissertations
Research Papers
Conference Presentations
Theses
Technical Blogs
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gptkbp:is_compared_to
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gptkb:Inception
gptkb:Mobile_Net
gptkb:Dense_Net
gptkb:Res_Net
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gptkbp:is_evaluated_by
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gptkb:CIFAR-10
gptkb:Stanford_Dogs
gptkb:CIFAR-100
Oxford Pets
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gptkbp:is_optimized_for
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gptkb:Adam
Mobile and Edge Devices
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gptkbp:is_part_of
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Open Source Projects
Computer Vision Libraries
Deep Learning Frameworks
AI Research Initiatives
Model Zoos
Efficient Net Architecture
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gptkbp:is_popular_in
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gptkb:scientific_community
Industry Applications
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gptkbp:is_used_for
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Feature Extraction
Fine-tuning
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gptkbp:is_used_in
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Computer Vision Tasks
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gptkbp:losses
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Cross-Entropy Loss
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gptkbp:normalization_technique
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gptkb:Batch_Normalization
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gptkbp:orbital_period
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5.3 million
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gptkbp:output_classes
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1000
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gptkbp:performance
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gptkb:Image_Net_Challenge
FLOPs
Model Efficiency
CVPR Competitions
ICCV Competitions
Neur IPS Competitions
Top-1 accuracy of 77.1% on Image Net
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gptkbp:predecessor
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Baseline CNNs
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gptkbp:provides_information_on
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gptkb:Image_Net
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gptkbp:scaling_method
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Compound Scaling
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gptkbp:speed
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Faster inference than previous models
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gptkbp:successor
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Efficient Net family
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gptkbp:supports
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Multi-Label Classification
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gptkbp:uses
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Depthwise Separable Convolutions
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gptkbp:uses_transfer_learning
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gptkb:True
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gptkbp:bfsParent
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gptkb:Efficient_Net
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gptkbp:bfsLayer
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5
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