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gptkbp:instance_of
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gptkb:television_channel
|
|
gptkbp:architectural_style
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Fully Convolutional
|
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gptkbp:based_on
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gptkb:Alex_Net
VGG Net
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|
gptkbp:can_be_used_with
|
Conditional Random Fields
|
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gptkbp:developed_by
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gptkb:Jonathan_Long
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gptkbp:has_expansion
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Standard CN Ns
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https://www.w3.org/2000/01/rdf-schema#label
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FCN (Fully Convolutional Network)
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gptkbp:improves
|
Semantic Segmentation
|
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gptkbp:influenced
|
Subsequent Segmentation Models
|
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gptkbp:input_output
|
gptkb:Images
Segmentation Maps
Pixel-wise Predictions
|
|
gptkbp:is_challenged_by
|
Adversarial Attacks
Noise in Images
Lighting Conditions
Occlusions
Variability in Object Appearance
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|
gptkbp:is_characterized_by
|
No Fully Connected Layers
|
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gptkbp:is_evaluated_by
|
gptkb:Cityscapes_Dataset
gptkb:Pascal_VOC_Dataset
gptkb:COCO_Dataset
Pixel Accuracy
AD E20 K Dataset
Mean Intersection over Union (m Io U)
Cam Vid Dataset
|
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
|
gptkbp:is_optimized_for
|
Real-time Applications
|
|
gptkbp:is_part_of
|
gptkb:viewpoint
gptkb:Artificial_Intelligence
|
|
gptkbp:is_popular_in
|
Deep Learning Community
|
|
gptkbp:is_related_to
|
gptkb:microprocessor
gptkb:Deep_Learning
Image Processing
Feature Extraction
|
|
gptkbp:is_used_for
|
Image Segmentation
|
|
gptkbp:is_used_in
|
Autonomous Driving
Object Detection
Medical Imaging
Instance Segmentation
Scene Understanding
Satellite Image Analysis
|
|
gptkbp:published_by
|
gptkb:2015
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|
gptkbp:requires
|
Large Datasets
|
|
gptkbp:sensor
|
Class Imbalance
|
|
gptkbp:training
|
gptkb:CEO
Backpropagation
|
|
gptkbp:uses
|
Skip Connections
|
|
gptkbp:utilizes
|
Deconvolution Layers
|
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gptkbp:bfsParent
|
gptkb:2_DU-Net
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gptkbp:bfsLayer
|
5
|