|
gptkbp:instance_of
|
gptkb:television_channel
|
|
gptkbp:bfsLayer
|
4
|
|
gptkbp:bfsParent
|
gptkb:Dense_Net
|
|
gptkbp:applies_to
|
gptkb:viewpoint
|
|
gptkbp:architectural_style
|
gptkb:Deep_Learning
|
|
gptkbp:based_on
|
gptkb:Res_Net
|
|
gptkbp:competes_with
|
gptkb:Dense_Net
|
|
gptkbp:developed_by
|
gptkb:Facebook_AI_Research
|
|
gptkbp:has
|
Multiple paths in architecture
|
|
gptkbp:has_achievements
|
State-of-the-art performance
|
|
gptkbp:has_variants
|
gptkb:Res_Ne_Xt-101
gptkb:Res_Ne_Xt-152
gptkb:Res_Ne_Xt-50
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Res Ne Xt
|
|
gptkbp:improves
|
Image Classification
|
|
gptkbp:introduced
|
gptkb:2017
|
|
gptkbp:is_adopted_by
|
Research institutions
Industry applications
|
|
gptkbp:is_available_on
|
gptkb:archive
Model repositories
|
|
gptkbp:is_cited_in
|
Numerous publications
|
|
gptkbp:is_considered_as
|
A state-of-the-art model
|
|
gptkbp:is_discussed_in
|
gptkb:Workshops
Conferences
|
|
gptkbp:is_documented_in
|
Research papers
Technical reports
|
|
gptkbp:is_evaluated_by
|
gptkb:CIFAR-10
gptkb:CIFAR-100
Top-1 accuracy
Top-5 accuracy
Places365
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:is_influenced_by
|
gptkb:Inception_Networks
gptkb:VGG_Networks
|
|
gptkbp:is_known_for
|
High accuracy
Efficient computation
|
|
gptkbp:is_optimized_for
|
Large-scale datasets
|
|
gptkbp:is_part_of
|
Deep Learning frameworks
Model zoo
|
|
gptkbp:is_popular_in
|
Academic research
Industry research
|
|
gptkbp:is_recognized_by
|
AI community
|
|
gptkbp:is_related_to
|
gptkb:Residual_Networks
|
|
gptkbp:is_supported_by
|
NVIDIAGP Us
TP Us
|
|
gptkbp:is_used_for
|
Image generation
Object detection
Semantic segmentation
|
|
gptkbp:is_used_in
|
gptkb:Image_Net_competition
|
|
gptkbp:performance
|
Other CNN architectures
|
|
gptkbp:uses
|
Cardinality
|
|
gptkbp:utilizes
|
Split-Transform-Merge strategy
|