gptkbp:instance_of
|
gptkb:software_framework
|
gptkbp:applies_to
|
Residual Learning
|
gptkbp:based_on
|
U-Net Architecture
|
gptkbp:can_be
|
CT Scans
MRI Scans
|
gptkbp:developed_by
|
gptkb:Research_Institute
Collaborative Efforts
Automated Diagnosis
|
gptkbp:enhances
|
Feature Propagation
|
gptkbp:features
|
Skip Connections
|
https://www.w3.org/2000/01/rdf-schema#label
|
V-Net++
|
gptkbp:improves
|
gptkb:V-Net
|
gptkbp:is_adopted_by
|
AI Researchers
|
gptkbp:is_available_on
|
gptkb:archive
|
gptkbp:is_cited_in
|
Numerous Research Papers
|
gptkbp:is_compatible_with
|
gptkb:Graphics_Processing_Unit
gptkb:Py_Torch
|
gptkbp:is_documented_in
|
Technical Papers
|
gptkbp:is_evaluated_by
|
gptkb:military_unit
Accuracy
Performance Metrics
User-Friendliness
Jaccard Index
Dice Coefficient
Public Benchmarks
Segmentation Quality
|
gptkbp:is_implemented_in
|
gptkb:Library
|
gptkbp:is_influenced_by
|
gptkb:Generative_Adversarial_Networks
Deep Learning Advances
|
gptkbp:is_optimized_for
|
GPU Processing
|
gptkbp:is_part_of
|
gptkb:hospital
gptkb:Photographer
Deep Learning Frameworks
Neural Network Models
AI Research Community
AI Tools for Medicine
Computer Vision Field
|
gptkbp:is_popular_in
|
Healthcare Research
|
gptkbp:is_related_to
|
Image Processing
|
gptkbp:is_scalable
|
Larger Datasets
|
gptkbp:is_supported_by
|
Community Contributions
|
gptkbp:is_tested_for
|
Robustness
Feature Extraction
Generalization
Tumor Detection
Synthetic Data
Real-World Data
Organ Segmentation
Clinical Applicability
Other Segmentation Models
|
gptkbp:is_used_by
|
gptkb:hospital
|
gptkbp:is_used_for
|
Image Analysis
Medical Image Segmentation
|
gptkbp:is_used_in
|
gptkb:legal_case
|
gptkbp:is_utilized_in
|
gptkb:healthcare_organization
Pathology
Image Reconstruction
|
gptkbp:presented_by
|
Conferences
|
gptkbp:requires
|
Large Amounts of Data
|
gptkbp:supports
|
Multi-Class Segmentation
|
gptkbp:training
|
3 D Medical Datasets
|
gptkbp:utilizes
|
3 D Convolutions
|
gptkbp:bfsParent
|
gptkb:V-Net
|
gptkbp:bfsLayer
|
5
|