gptkbp:instance_of
|
gptkb:microprocessor
|
gptkbp:adapted_into
|
different modalities
|
gptkbp:applies_to
|
3 D convolutions
|
gptkbp:architectural_style
|
encoder-decoder
|
gptkbp:based_on
|
fully convolutional networks
|
gptkbp:collaborated_with
|
research institutions
|
gptkbp:competes_with
|
gptkb:Alumni_Association
|
gptkbp:developed_by
|
gptkb:Microsoft_Research
|
gptkbp:has_achievements
|
state-of-the-art results
|
gptkbp:has_programs
|
neurology
oncology
radiology
|
gptkbp:has_variants
|
gptkb:V-Net++
|
https://www.w3.org/2000/01/rdf-schema#label
|
V-Net
|
gptkbp:improves
|
medical image analysis
|
gptkbp:input_output
|
3 D volumetric data
segmentation maps
|
gptkbp:introduced
|
gptkb:2016
|
gptkbp:is_cited_in
|
research articles
|
gptkbp:is_documented_in
|
academic papers
|
gptkbp:is_enhanced_by
|
post-processing techniques
|
gptkbp:is_evaluated_by
|
traditional methods
benchmark datasets
clinical applications
medical imaging datasets
|
gptkbp:is_implemented_in
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
gptkbp:is_influenced_by
|
gptkb:Dense_Net
gptkb:Res_Net
|
gptkbp:is_integrated_with
|
other AI systems
|
gptkbp:is_known_for
|
high accuracy
robustness to noise
|
gptkbp:is_optimized_for
|
GPU processing
|
gptkbp:is_part_of
|
deep learning frameworks
medical imaging pipelines
|
gptkbp:is_popular_in
|
computer vision community
|
gptkbp:is_recognized_for
|
innovation in AI
|
gptkbp:is_scalable
|
large datasets
|
gptkbp:is_supported_by
|
open-source community
|
gptkbp:is_tested_for
|
synthetic data
real-world data
|
gptkbp:is_used_for
|
3 D image segmentation
|
gptkbp:is_used_in
|
surgical planning
image-guided therapy
automated diagnosis
|
gptkbp:is_utilized_in
|
gptkb:Insurance_Company
|
gptkbp:performance
|
other segmentation networks
|
gptkbp:requires
|
large annotated datasets
|
gptkbp:suitable_for
|
real-time applications
|
gptkbp:training
|
transfer learning
data augmentation techniques
|
gptkbp:utilizes
|
skip connections
|
gptkbp:bfsParent
|
gptkb:3_DU-Net
|
gptkbp:bfsLayer
|
4
|