|
gptkbp:instance_of
|
gptkb:television_channel
|
|
gptkbp:bfsLayer
|
3
|
|
gptkbp:bfsParent
|
gptkb:viewpoint
gptkb:television_channel
|
|
gptkbp:adapted_into
|
Real-time Applications
|
|
gptkbp:applies_to
|
Image Classification
|
|
gptkbp:architectural_style
|
gptkb:Deep_Learning
skip connections
|
|
gptkbp:composed_of
|
Residual Blocks
|
|
gptkbp:developed_by
|
gptkb:Microsoft_Research
|
|
gptkbp:established
|
Re LU
|
|
gptkbp:has_achievements
|
top-5 accuracy
State-of-the-art performance
state-of-the-art performance on Image Net
|
|
gptkbp:has_variants
|
gptkb:Res_Net-101
gptkb:Res_Net-152
gptkb:Res_Net-50
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Res Net
|
|
gptkbp:improves
|
Training of Deep Networks
|
|
gptkbp:influenced
|
Subsequent Architectures
|
|
gptkbp:introduced
|
gptkb:2015
|
|
gptkbp:is_cited_in
|
Numerous Research Papers
|
|
gptkbp:is_compared_to
|
gptkb:Dense_Net
gptkb:Inception_Network
VGG Net
|
|
gptkbp:is_evaluated_by
|
gptkb:CIFAR-10
gptkb:CIFAR-100
gptkb:COCO_Dataset
gptkb:Image_Net_Dataset
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Keras
gptkb:Py_Torch
|
|
gptkbp:is_known_for
|
high accuracy
Skip Connections
efficient training
high performance on benchmarks
flexibility in architecture design
deep residual learning
deep architectures
|
|
gptkbp:is_optimized_for
|
Stochastic Gradient Descent
|
|
gptkbp:is_part_of
|
gptkb:Deep_Residual_Learning
AI Research Community
|
|
gptkbp:is_popular_in
|
gptkb:viewpoint
deep learning community
|
|
gptkbp:is_scalable
|
Larger Datasets
|
|
gptkbp:is_supported_by
|
NVIDIAGP Us
TP Us
|
|
gptkbp:is_used_for
|
Facial Recognition
Feature Extraction
Image Retrieval
transfer learning
Medical Image Analysis
|
|
gptkbp:is_used_in
|
gptkb:Autonomous_Vehicles
gptkb:sports_team
gptkb:software
gptkb:robot
Object Detection
Sentiment Analysis
Image Segmentation
Surveillance Systems
Agricultural Monitoring
Social Media Analysis
Content Moderation
object detection
video analysis
Retail Analytics
image segmentation
Smart Cameras
face recognition
|
|
gptkbp:known_for
|
residual learning
|
|
gptkbp:performance
|
Deep Learning Models
|
|
gptkbp:publishes
|
Over 1000
|
|
gptkbp:security_features
|
Overfitting
|
|
gptkbp:supports
|
gptkb:streaming_service
|
|
gptkbp:training
|
gptkb:Image_Net
Varies by Configuration
|
|
gptkbp:used_in
|
image classification
|
|
gptkbp:uses
|
Residual Learning
|
|
gptkbp:winner
|
gptkb:ILSVRC_2015
|