Statements (29)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
deep convolutional neural network
|
| gptkbp:activatedBy |
gptkb:ReLU
|
| gptkbp:architecture |
residual network
|
| gptkbp:author |
gptkb:Shaoqing_Ren
gptkb:Xiangyu_Zhang gptkb:Jian_Sun gptkb:Kaiming_He |
| gptkbp:basedOn |
residual learning
|
| gptkbp:bench |
gptkb:ImageNet
|
| gptkbp:category |
computer vision model
|
| gptkbp:contains |
residual blocks
|
| gptkbp:developedBy |
gptkb:Microsoft_Research
|
| https://www.w3.org/2000/01/rdf-schema#label |
ResNet-101
|
| gptkbp:improves |
gptkb:VGG-19
|
| gptkbp:inputImageSize |
224x224
|
| gptkbp:introduced |
gptkb:Deep_Residual_Learning_for_Image_Recognition
|
| gptkbp:introducedIn |
2015
|
| gptkbp:level |
101
|
| gptkbp:notableFeature |
skip connections
|
| gptkbp:openSource |
gptkb:TensorFlow
gptkb:Keras gptkb:PyTorch |
| gptkbp:parameter |
44.5 million
|
| gptkbp:pretrainedWeightsAvailable |
yes
|
| gptkbp:usedFor |
image classification
object detection semantic segmentation |
| gptkbp:bfsParent |
gptkb:Residual_Network
|
| gptkbp:bfsLayer |
7
|