|
gptkbp:instance_of
|
gptkb:microprocessor
|
|
gptkbp:bfsLayer
|
7
|
|
gptkbp:bfsParent
|
gptkb:Cresnet_18.0
gptkb:Cresnet_19.0
|
|
gptkbp:applies_to
|
gptkb:television_channel
|
|
gptkbp:based_on
|
Skip Connections
|
|
gptkbp:benefits
|
Very Deep Networks
|
|
gptkbp:competes_with
|
gptkb:Dense_Net
|
|
gptkbp:composed_of
|
Residual Blocks
|
|
gptkbp:developed_by
|
gptkb:Kaiming_He
|
|
gptkbp:enhances
|
Gradient Flow
|
|
gptkbp:has_achievements
|
State-of-the-art Performance
|
|
gptkbp:has_variants
|
gptkb:Res_Net-101
gptkb:Res_Net-152
gptkb:Res_Net-50
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Residual Network
|
|
gptkbp:improves
|
Training of Deep Networks
|
|
gptkbp:introduced
|
gptkb:2015
|
|
gptkbp:is_adopted_by
|
gptkb:Research_Institute
Autonomous Driving
Facial Recognition
Medical Imaging
Video Analysis
|
|
gptkbp:is_cited_in
|
Numerous Research Papers
|
|
gptkbp:is_compared_to
|
Traditional CN Ns
|
|
gptkbp:is_considered_as
|
Deep Architecture
|
|
gptkbp:is_designed_to
|
Facilitate Training
|
|
gptkbp:is_evaluated_by
|
gptkb:CIFAR-10
gptkb:CIFAR-100
gptkb:Image_Net_Dataset
Loss Function
Top-1 Accuracy
Top-5 Accuracy
|
|
gptkbp:is_explored_in
|
gptkb:software_framework
gptkb:Graph_Neural_Networks
gptkb:Neural_Architecture_Search
Unsupervised Learning
Adversarial Training
Generative Models
Multi-task Learning
Model Compression
Self-supervised Learning
Few-shot Learning
Zero-shot Learning
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
Convolutional Layers
Activation Functions
|
|
gptkbp:is_influenced_by
|
Highway Networks
|
|
gptkbp:is_known_for
|
Identity Mapping
Skip Connections
|
|
gptkbp:is_optimized_for
|
gptkb:benchmark
|
|
gptkbp:is_part_of
|
Deep Residual Learning Framework
|
|
gptkbp:is_popular_in
|
gptkb:viewpoint
|
|
gptkbp:is_related_to
|
gptkb:Deep_Learning
|
|
gptkbp:is_supported_by
|
NVIDIAGP Us
TP Us
|
|
gptkbp:is_tested_for
|
Various Datasets
|
|
gptkbp:is_used_for
|
Object Detection
Semantic Segmentation
|
|
gptkbp:is_used_in
|
gptkb:streaming_service
Feature Extraction
|
|
gptkbp:is_utilized_in
|
Real-time Applications
|
|
gptkbp:performance
|
Image Classification Tasks
|
|
gptkbp:reduces
|
Vanishing Gradient Problem
|
|
gptkbp:training
|
Stochastic Gradient Descent
|
|
gptkbp:used_in
|
Image Classification
|
|
gptkbp:utilizes
|
gptkb:Batch_Normalization
|