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gptkbp:instance_of
|
gptkb:microprocessor
|
|
gptkbp:based_on
|
deep learning principles
|
|
gptkbp:can_be_used_with
|
gptkb:Res_Net_architecture
Inception architecture
|
|
gptkbp:developed_by
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gptkb:Job_Search_Engine
|
|
gptkbp:has
|
pre-trained models
multiple layers
|
|
gptkbp:has_achievements
|
high accuracy on Image Net
|
|
https://www.w3.org/2000/01/rdf-schema#label
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Inception-Res Net v2
|
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gptkbp:improves
|
training speed
|
|
gptkbp:introduced
|
gptkb:2016
|
|
gptkbp:is_compatible_with
|
various datasets
|
|
gptkbp:is_designed_for
|
high performance
|
|
gptkbp:is_evaluated_by
|
gptkb:Image_Net
gptkb:CIFAR-10
gptkb:CIFAR-100
cross-validation
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:is_influenced_by
|
gptkb:Res_Ne_Xt
|
|
gptkbp:is_known_for
|
high precision
efficient computation
state-of-the-art performance
robustness to noise
reducing overfitting
|
|
gptkbp:is_optimized_for
|
speed and accuracy
|
|
gptkbp:is_part_of
|
AI research community
model zoo
Keras applications
|
|
gptkbp:is_popular_in
|
gptkb:physicist
gptkb:academic_research
|
|
gptkbp:is_related_to
|
gptkb:Dense_Net
|
|
gptkbp:is_scalable
|
larger models
|
|
gptkbp:is_used_for
|
image classification
|
|
gptkbp:is_used_in
|
gptkb:engine
image recognition
object detection
video analysis
facial recognition
image generation
image retrieval
semantic segmentation
medical image analysis
style transfer
computer vision tasks
transfer learning tasks
|
|
gptkbp:performance
|
other architectures
|
|
gptkbp:reduces
|
model size
|
|
gptkbp:suitable_for
|
large datasets
real-time applications
|
|
gptkbp:supports
|
transfer learning
|
|
gptkbp:training
|
stochastic gradient descent
GP Us
|
|
gptkbp:utilizes
|
batch normalization
skip connections
|
|
gptkbp:variant
|
gptkb:Res_Net
gptkb:Inception_v3
|
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gptkbp:bfsParent
|
gptkb:Inception_v4
|
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gptkbp:bfsLayer
|
7
|