|
gptkbp:instance_of
|
gptkb:television_channel
|
|
gptkbp:architectural_style
|
gptkb:Deep_Learning
|
|
gptkbp:coat_of_arms
|
152
|
|
gptkbp:developed_by
|
gptkb:Microsoft_Research
|
|
gptkbp:established
|
Re LU
|
|
gptkbp:has_achievements
|
gptkb:Image_Net_Challenge
|
|
gptkbp:has_method
|
60 million
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Res Net-152
|
|
gptkbp:input_output
|
224x224
|
|
gptkbp:is_adopted_by
|
gptkb:film_production_company
|
|
gptkbp:is_analyzed_in
|
gptkb:battle
|
|
gptkbp:is_compared_to
|
gptkb:Inception
gptkb:Dense_Net
VGG Net
|
|
gptkbp:is_evaluated_by
|
gptkb:CIFAR-10
gptkb:COCO
gptkb:CIFAR-100
Cityscapes
PASCALVOC
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:is_known_for
|
gptkb:streaming_service
gptkb:Deep_Residual_Learning
High Accuracy
Fine-tuning
Skip Connections
Efficient Training
Feature Reuse
|
|
gptkbp:is_optimized_for
|
Parallel Processing
|
|
gptkbp:is_part_of
|
gptkb:Res_Net_Family
Deep Learning Frameworks
|
|
gptkbp:is_popular_in
|
Academic Publications
|
|
gptkbp:is_supported_by
|
NVIDIAGP Us
TP Us
|
|
gptkbp:is_used_in
|
gptkb:museum
Image Classification
Object Detection
Self-Driving Cars
Image Segmentation
Medical Imaging
Face Recognition
Generative Models
|
|
gptkbp:localization
|
gptkb:theorem
|
|
gptkbp:performance
|
Computer Vision Tasks
|
|
gptkbp:predecessor
|
gptkb:Res_Net-101
|
|
gptkbp:resolution
|
1000 classes
|
|
gptkbp:successor
|
gptkb:Res_Net-164
|
|
gptkbp:training
|
gptkb:Adam_Optimizer
gptkb:Image_Net_Dataset
Stochastic Gradient Descent
|
|
gptkbp:uses
|
Average Pooling
Residual Learning
|
|
gptkbp:year_created
|
gptkb:2015
|
|
gptkbp:bfsParent
|
gptkb:Res_Net
|
|
gptkbp:bfsLayer
|
4
|