|
gptkbp:instance_of
|
gptkb:neural_networks
|
|
gptkbp:achieved_top5_accuracy
|
93.3% on Image Net
|
|
gptkbp:architecture
|
gptkb:Deep_Learning
|
|
gptkbp:based_on
|
Residual Learning
|
|
gptkbp:depth
|
101 layers
|
|
gptkbp:developed_by
|
gptkb:Microsoft_Research
|
|
gptkbp:has_input_size
|
224x224 pixels
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Res Net-101
|
|
gptkbp:introduced_in
|
gptkb:2015
|
|
gptkbp:is_adopted_by
|
Kaggle Competitions
|
|
gptkbp:is_applied_in
|
Object Detection
Semantic Segmentation
|
|
gptkbp:is_cited_in
|
Research Papers
|
|
gptkbp:is_compatible_with
|
gptkb:Tensor_Flow
gptkb:Py_Torch
|
|
gptkbp:is_evaluated_by
|
gptkb:CIFAR-10
gptkb:SVHN
gptkb:Tiny_Image_Net
gptkb:Fashion_MNIST
gptkb:CIFAR-100
gptkb:COCO_Dataset
Places365
Oxford Pets
|
|
gptkbp:is_influential_in
|
Deep Learning Research
|
|
gptkbp:is_known_for
|
High Performance
Feature Extraction
High Accuracy
Fine-tuning
Model Compression
Residual Blocks
|
|
gptkbp:is_optimized_for
|
GPU Training
|
|
gptkbp:is_part_of
|
gptkb:Image_Net_Challenge
gptkb:Res_Net_Family
|
|
gptkbp:is_popular_in
|
gptkb:Computer_Vision
|
|
gptkbp:is_supported_by
|
Community Contributions
Open Source Libraries
|
|
gptkbp:is_trained_in
|
gptkb:Image_Net_Dataset
|
|
gptkbp:is_used_in
|
gptkb:Augmented_Reality
gptkb:art
gptkb:Autonomous_Vehicles
gptkb:virtual_reality
gptkb:Natural_Language_Processing
gptkb:stage_adaptation
gptkb:robotics
Anomaly Detection
Image Generation
Sentiment Analysis
Facial Recognition
Medical Imaging
Video Analysis
|
|
gptkbp:performance
|
Deep Learning Models
Image Classification Tasks
77.0% on Image Net
|
|
gptkbp:predecessor
|
gptkb:Res_Net-50
|
|
gptkbp:successor
|
gptkb:Res_Net-152
|
|
gptkbp:used_for
|
Image Classification
|
|
gptkbp:uses
|
gptkb:Batch_Normalization
Re LU Activation Function
|
|
gptkbp:utilizes
|
Skip Connections
|
|
gptkbp:bfsParent
|
gptkb:Res_Net
|
|
gptkbp:bfsLayer
|
5
|