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gptkbp:instance_of
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gptkb:Model
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gptkbp:applies_to
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semantic segmentation
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gptkbp:based_on
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gptkb:television_channel
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gptkbp:developed_by
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gptkb:Google_Research
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gptkbp:first_introduced
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gptkb:2016
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gptkbp:has_achievements
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state-of-the-art performance
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gptkbp:has_programs
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augmented reality
satellite imagery analysis
urban scene understanding
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https://www.w3.org/2000/01/rdf-schema#label
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Deep Lab family of models
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gptkbp:includes
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gptkb:Deep_Lab_v1
gptkb:Deep_Lab_v2
gptkb:Deep_Lab_v3
gptkb:Deep_Lab_v3+
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gptkbp:is_compatible_with
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gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
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gptkbp:is_documented_in
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gptkb:archive
tutorials
online courses
research articles
technical reports
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gptkbp:is_evaluated_by
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gptkb:COCO_dataset
gptkb:Cityscapes_dataset
AD E20 K dataset
PASCALVOC dataset
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gptkbp:is_influenced_by
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gptkb:Alumni_Association
gptkb:Seg_Net
Fully Convolutional Networks
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gptkbp:is_open_source
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gptkb:theorem
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gptkbp:is_optimized_for
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real-time inference
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gptkbp:is_part_of
|
deep learning community
computer vision field
|
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gptkbp:is_scalable
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high-resolution images
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gptkbp:is_supported_by
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community contributions
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gptkbp:is_used_by
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gptkb:physicist
gptkb:software
data scientists
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gptkbp:is_used_in
|
gptkb:robot
autonomous driving
medical image analysis
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gptkbp:performance
|
pixel accuracy
mean Intersection over Union (m Io U)
|
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gptkbp:publishes
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gptkb:Encoder-Decoder_with_Atrous_Separable_Convolution_for_Semantic_Image_Segmentation
Deep Lab v3: Rethinking Atrous Convolution for Semantic Image Segmentation
Deep Lab v3+: Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Deep Lab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Conditional Random Fields
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gptkbp:requires
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large memory capacity
GPU for training
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gptkbp:security_features
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image noise
occlusions
lighting variations
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gptkbp:supports
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multi-scale feature extraction
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gptkbp:training
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large-scale datasets
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gptkbp:uses
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gptkb:Atrous_Convolution
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gptkbp:utilizes
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Conditional Random Fields
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gptkbp:bfsParent
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gptkb:Deep_Lab_v3+
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gptkbp:bfsLayer
|
5
|