ImageNet CNN
E899061
ImageNet CNN is a convolutional neural network model trained on the large-scale ImageNet dataset, commonly used as a powerful pretrained feature extractor for various computer vision tasks.
All labels observed (1)
| Label | Occurrences |
|---|---|
| ImageNet CNN canonical | 1 |
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
convolutional neural network model
ⓘ
deep learning model ⓘ |
| appliedTo |
fine-grained classification
ⓘ
image retrieval ⓘ object detection ⓘ semantic segmentation ⓘ visual recognition ⓘ |
| associatedWith | ImageNet Large Scale Visual Recognition Challenge NERFINISHED ⓘ |
| basedOn | convolutional neural networks ⓘ |
| commonlyUsedAs |
feature extractor
ⓘ
initialization for downstream models ⓘ pretrained backbone ⓘ |
| enables |
faster convergence in downstream tasks
ⓘ
improved accuracy on small datasets ⓘ transfer of visual representations ⓘ |
| evaluationMetric |
top-1 accuracy
ⓘ
top-5 accuracy ⓘ |
| hasAdvantage |
captures generic low-level and mid-level visual patterns
ⓘ
reduces need for large labeled datasets in downstream tasks ⓘ |
| hasComponent |
convolutional layers
ⓘ
fully connected layers ⓘ nonlinear activation functions ⓘ pooling layers ⓘ |
| hasDomain |
artificial intelligence
ⓘ
computer vision ⓘ machine learning ⓘ |
| hasProperty |
general-purpose visual features
ⓘ
hierarchical feature representations ⓘ high-dimensional feature embeddings ⓘ large-scale pretraining ⓘ learned visual features ⓘ supervised learning ⓘ |
| hasTrainingObjective | image classification on ImageNet ⓘ |
| inputType |
RGB images
ⓘ
natural images ⓘ |
| outputType |
class probabilities
ⓘ
feature vectors ⓘ |
| representationType | deep visual features ⓘ |
| trainedOn | ImageNet dataset NERFINISHED ⓘ |
| trainedWith |
backpropagation
ⓘ
data augmentation ⓘ stochastic gradient descent ⓘ |
| usedFor |
computer vision tasks
ⓘ
feature extraction ⓘ image classification ⓘ transfer learning ⓘ |
| usedIn |
academic research
ⓘ
industrial computer vision applications ⓘ |
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.