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.

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ImageNet CNN canonical 1

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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

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