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gptkbp:instance_of
|
gptkb:television_channel
|
|
gptkbp:adapted_into
|
various architectures
|
|
gptkbp:applies_to
|
gptkb:Photographer
satellite imagery
autonomous driving
|
|
gptkbp:architectural_style
|
gptkb:television_channel
|
|
gptkbp:based_on
|
gptkb:FCN-32s
|
|
gptkbp:developed_by
|
gptkb:Jonathan_Long
|
|
gptkbp:enhances
|
pixel-wise classification
|
|
gptkbp:has
|
high parameter efficiency
multi-scale predictions
|
|
gptkbp:has_achievements
|
segmentation accuracy
|
|
gptkbp:has_expansion
|
gptkb:FCN-8
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
FCN-8s
|
|
gptkbp:improves
|
traditional CN Ns
|
|
gptkbp:input_output
|
gptkb:Photographer
segmentation map
|
|
gptkbp:is_compared_to
|
gptkb:Alumni_Association
gptkb:Deep_Lab
gptkb:Seg_Net
|
|
gptkbp:is_evaluated_by
|
gptkb:COCO
Cityscapes
PASCALVOC
mean Intersection over Union (m Io U)
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:is_known_for
|
real-time performance
|
|
gptkbp:is_part_of
|
deep learning frameworks
|
|
gptkbp:is_popular_in
|
computer vision community
|
|
gptkbp:is_used_for
|
object detection
semantic segmentation
|
|
gptkbp:is_used_in
|
image segmentation competitions
|
|
gptkbp:published_by
|
gptkb:2015
|
|
gptkbp:requires
|
GPU acceleration
|
|
gptkbp:training
|
labeled datasets
|
|
gptkbp:uses
|
deconvolution layers
|
|
gptkbp:utilizes
|
skip connections
|
|
gptkbp:bfsParent
|
gptkb:television_channel
|
|
gptkbp:bfsLayer
|
3
|