|
gptkbp:instance_of
|
gptkb:cosmic_ray_detector
|
|
gptkbp:applies_to
|
computer vision
|
|
gptkbp:developed_by
|
gptkb:Google
|
|
gptkbp:enhances
|
object boundary detection
|
|
gptkbp:features
|
dense prediction
|
|
gptkbp:has_achieved
|
state-of-the-art performance
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Deep Lab v2
|
|
gptkbp:improves
|
semantic segmentation
|
|
gptkbp:is_adopted_by
|
research institutions
tech companies
|
|
gptkbp:is_based_on
|
gptkb:Deep_Lab
|
|
gptkbp:is_compatible_with
|
gptkb:NVIDIA_GPUs
gptkb:TPUs
|
|
gptkbp:is_documented_in
|
research papers
tutorials
online courses
technical reports
Git Hub repositories
|
|
gptkbp:is_evaluated_by
|
gptkb:PASCAL_VOC_dataset
gptkb:SUN_RGB-D_dataset
gptkb:COCO_dataset
gptkb:Cityscapes_dataset
gptkb:KITTI_dataset
gptkb:ADE20_K_dataset
|
|
gptkbp:is_implemented_in
|
gptkb:Tensor_Flow
|
|
gptkbp:is_influenced_by
|
gptkb:Res_Net
Fully Convolutional Networks
Inception networks
|
|
gptkbp:is_known_for
|
high accuracy
flexibility in architecture
robustness to occlusion
|
|
gptkbp:is_part_of
|
gptkb:Deep_Lab_family
machine learning applications
deep learning frameworks
AI research community
artificial intelligence technologies
computer vision benchmarks
|
|
gptkbp:is_popular_in
|
gptkb:academic_research
industry applications
|
|
gptkbp:is_related_to
|
gptkb:Deep_Lab_v3
gptkb:Deep_Lab_v3+
|
|
gptkbp:is_supported_by
|
community contributions
|
|
gptkbp:is_trained_in
|
large datasets
|
|
gptkbp:is_used_for
|
gptkb:medical_imaging
augmented reality
image classification
object detection
video analysis
feature extraction
image analysis
scene understanding
|
|
gptkbp:is_used_in
|
autonomous driving
image segmentation competitions
|
|
gptkbp:release_year
|
gptkb:2017
|
|
gptkbp:requires
|
GPU acceleration
|
|
gptkbp:supports
|
real-time applications
|
|
gptkbp:uses
|
atrous convolution
|
|
gptkbp:utilizes
|
multi-scale context
|
|
gptkbp:bfsParent
|
gptkb:Deep_Lab
|
|
gptkbp:bfsLayer
|
5
|