|
gptkbp:instance_of
|
gptkb:microprocessor
|
|
gptkbp:applies_to
|
image classification
|
|
gptkbp:based_on
|
gptkb:Res_Net
|
|
gptkbp:developed_by
|
gptkb:Facebook_AI_Research
|
|
gptkbp:has
|
multiple branches
|
|
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 architecture
|
|
gptkbp:improves
|
model accuracy
|
|
gptkbp:introduced
|
gptkb:2017
|
|
gptkbp:is_adopted_by
|
gptkb:Research_Institute
|
|
gptkbp:is_characterized_by
|
modular design
|
|
gptkbp:is_compared_to
|
VGG Net
|
|
gptkbp:is_evaluated_by
|
gptkb:Fashion-MNIST
gptkb:CIFAR-10
gptkb:Stanford_Dogs
gptkb:COCO_dataset
gptkb:Image_Net_dataset
gptkb:CIFAR-100
Places365
Oxford Pets
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:is_influenced_by
|
gptkb:Dense_Net
|
|
gptkbp:is_known_for
|
high accuracy
low latency
scalability
modular architecture
robustness
high efficiency
generalization ability
low computational cost
|
|
gptkbp:is_optimized_for
|
GPU performance
|
|
gptkbp:is_part_of
|
deep learning frameworks
|
|
gptkbp:is_similar_to
|
Inception architecture
|
|
gptkbp:is_used_for
|
video analysis
feature extraction
image retrieval
face recognition
|
|
gptkbp:is_used_in
|
gptkb:Photographer
gptkb:robot
augmented reality
autonomous driving
object detection
image segmentation
scene understanding
semantic segmentation
image synthesis
style transfer
computer vision tasks
3 D object recognition
|
|
gptkbp:supports
|
transfer learning
|
|
gptkbp:training
|
large datasets
|
|
gptkbp:uses
|
cardinality
|
|
gptkbp:utilizes
|
split-transform-merge strategy
|
|
gptkbp:bfsParent
|
gptkb:Inception-Res_Net
|
|
gptkbp:bfsLayer
|
5
|