|
gptkbp:instance_of
|
gptkb:television_channel
|
|
gptkbp:bfsLayer
|
5
|
|
gptkbp:bfsParent
|
gptkb:Deep_Lab_v3
|
|
gptkbp:adapted_into
|
Different Domains
|
|
gptkbp:applies_to
|
Image Processing
|
|
gptkbp:based_on
|
Deep Learning Techniques
Fully Convolutional Networks
|
|
gptkbp:developed_by
|
gptkb:Google_Research
|
|
gptkbp:enhances
|
Segmentation Accuracy
|
|
gptkbp:first_introduced
|
gptkb:2016
|
|
gptkbp:has_achievements
|
State-of-the-art Performance
|
|
gptkbp:has_variants
|
gptkb:Deep_Labv1
gptkb:Deep_Labv2
gptkb:Deep_Labv3
gptkb:Deep_Labv3+
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Deep Lab architecture
|
|
gptkbp:improves
|
Feature Extraction
|
|
gptkbp:includes
|
Conditional Random Fields
|
|
gptkbp:is_cited_in
|
Academic Journals
|
|
gptkbp:is_compatible_with
|
gptkb:streaming_service
|
|
gptkbp:is_discussed_in
|
Conferences
|
|
gptkbp:is_enhanced_by
|
Post-Processing Techniques
|
|
gptkbp:is_evaluated_by
|
Cityscapes
Pixel Accuracy
PASCALVOC
AD E20 K
Mean Intersection over Union (m Io U)
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:is_influenced_by
|
gptkb:Res_Net
gptkb:Xception
|
|
gptkbp:is_known_for
|
Real-time Segmentation
|
|
gptkbp:is_optimized_for
|
gptkb:smartphone
|
|
gptkbp:is_part_of
|
Deep Learning Frameworks
|
|
gptkbp:is_popular_in
|
Computer Vision Community
|
|
gptkbp:is_related_to
|
gptkb:microprocessor
Object Detection
Feature Maps
Image Segmentation
|
|
gptkbp:is_supported_by
|
Research Papers
|
|
gptkbp:is_used_for
|
Semantic Segmentation
|
|
gptkbp:is_used_in
|
gptkb:Autonomous_Vehicles
gptkb:software
Medical Imaging
|
|
gptkbp:is_utilized_in
|
gptkb:musician
gptkb:noble_title
gptkb:sports_team
gptkb:robot
gptkb:metropolitan_area
gptkb:video_game_series
gptkb:brand
Environmental Monitoring
Facial Recognition
Image Editing
Geospatial Analysis
Disaster Management
Wildlife Conservation
Scene Understanding
Smart Surveillance
|
|
gptkbp:requires
|
High Computational Resources
|
|
gptkbp:supports
|
Multi-Class Segmentation
|
|
gptkbp:training
|
Large Datasets
|
|
gptkbp:uses
|
Multi-Scale Context
|
|
gptkbp:utilizes
|
gptkb:Atrous_Convolution
|