Statements (46)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Photographer
|
| gptkbp:application |
super-resolution
|
| gptkbp:architect |
convolutional neural network
|
| gptkbp:completed |
state-of-the-art results
|
| gptkbp:developedBy |
gptkb:J._Kim
|
| gptkbp:has |
multiple layers
|
| https://www.w3.org/2000/01/rdf-schema#label |
VDSR
|
| gptkbp:improves |
image quality
|
| gptkbp:influencedBy |
DNN
|
| gptkbp:inputOutput |
low-resolution images
|
| gptkbp:isAttendedBy |
industry
academia |
| gptkbp:isBasedOn |
residual learning
|
| gptkbp:isConsidered |
a benchmark model
|
| gptkbp:isDiscussedIn |
workshops
conferences |
| gptkbp:isDocumentedIn |
research papers
theses |
| gptkbp:isEvaluatedBy |
PSNR
SSIM real-world images synthetic images |
| gptkbp:isLocatedIn |
gptkb:PyTorch
TensorFlow |
| gptkbp:isOptimizedFor |
accuracy
speed |
| gptkbp:isPartOf |
gptkb:EDSR
machine learning computer vision AI applications |
| gptkbp:isPopularIn |
research community
|
| gptkbp:isRelatedTo |
GANs
|
| gptkbp:isSupportedBy |
gptkb:AMD
NVIDIA |
| gptkbp:isTrainedIn |
benchmark datasets
|
| gptkbp:isUsedFor |
video upscaling
|
| gptkbp:isUsedIn |
satellite imagery
photography medical imaging video games image enhancement |
| gptkbp:powerOutput |
high-resolution images
|
| gptkbp:relatedTo |
gptkb:SRCNN
|
| gptkbp:requires |
training data
|
| gptkbp:uses |
deep learning
|
| gptkbp:yearEstablished |
2016
|