Deep Labv2

GPTKB entity

Statements (60)
Predicate Object
gptkbp:instance_of gptkb:Model
gptkbp:bfsLayer 4
gptkbp:bfsParent gptkb:Deep_Lab
gptkbp:applies_to computer vision
gptkbp:based_on gptkb:Res_Net_architecture
gptkb:Xception_architecture
gptkb:Deep_Lab
gptkbp:developed_by gptkb:Job_Search_Engine
gptkbp:enhances feature extraction
gptkbp:has_achievements state-of-the-art performance
https://www.w3.org/2000/01/rdf-schema#label Deep Labv2
gptkbp:improves semantic segmentation
gptkbp:is_adopted_by gptkb:academic_research
industry applications
gptkbp:is_compatible_with gptkb:Keras
gptkb:Py_Torch
gptkbp:is_documented_in research papers
Git Hub repositories
gptkbp:is_evaluated_by gptkb:COCO_dataset
gptkb:Cam_Vid_dataset
gptkb:Cityscapes_dataset
LIP dataset
AD E20 K dataset
PASCALVOC dataset
SBD dataset
gptkbp:is_implemented_in gptkb:Graphics_Processing_Unit
gptkbp:is_influenced_by gptkb:Alumni_Association
gptkb:FCN_(Fully_Convolutional_Networks)
gptkb:Seg_Net
gptkbp:is_known_for high accuracy
real-time performance
robustness to noise
flexibility in architecture
adaptability to different tasks
gptkbp:is_optimized_for GPU acceleration
gptkbp:is_part_of gptkb:Deep_Lab_family
deep learning frameworks
AI advancements
computer vision research
machine learning innovations
gptkbp:is_related_to gptkb:Deep_Labv3
gptkb:Deep_Labv3+
gptkbp:is_supported_by community contributions
research grants
collaborations with universities
gptkbp:is_used_for object detection
image segmentation tasks
gptkbp:is_used_in gptkb:musician
gptkb:Photographer
gptkb:robot
augmented reality
autonomous driving
image analysis
scene understanding
gptkbp:provides pixel-level classification
gptkbp:release_year gptkb:2017
gptkbp:supports multi-scale context
gptkbp:training large datasets
gptkbp:uses atrous convolution
gptkbp:utilizes fully convolutional networks