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gptkbp:instanceOf
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gptkb:convolutional_neural_network
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|
gptkbp:application
|
face recognition
image classification
object detection
semantic segmentation
|
|
gptkbp:arXivID
|
1704.04861
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gptkbp:author
|
gptkb:Bo_Chen
gptkb:Andrew_G._Howard
gptkb:Dmitry_Kalenichenko
gptkb:Hartwig_Adam
gptkb:Marco_Andreetto
gptkb:Menglong_Zhu
gptkb:Tobias_Weyand
gptkb:Weijun_Wang
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|
gptkbp:availableOn
|
gptkb:PyTorch_Hub
gptkb:TensorFlow_Hub
|
|
gptkbp:category
|
gptkb:model
computer vision
|
|
gptkbp:designedFor
|
mobile devices
embedded vision applications
|
|
gptkbp:developedBy
|
gptkb:Google
|
|
gptkbp:digestSize
|
224x224
|
|
gptkbp:frameworksAvailableIn
|
gptkb:TensorFlow
gptkb:Keras
gptkb:PyTorch
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
MobileNet
|
|
gptkbp:introducedIn
|
2017
|
|
gptkbp:license
|
gptkb:Apache_License_2.0
|
|
gptkbp:notableFeature
|
low computational cost
lightweight architecture
suitable for real-time applications
|
|
gptkbp:notablePublication
|
gptkb:MobileNets:_Efficient_Convolutional_Neural_Networks_for_Mobile_Vision_Applications
|
|
gptkbp:notableRelease
|
gptkb:MobileNetV1
gptkb:MobileNetV2
gptkb:MobileNetV3
|
|
gptkbp:parameter
|
4.2 million (MobileNetV1, 1.0 width multiplier, 224x224 input)
|
|
gptkbp:publishedIn
|
gptkb:arXiv
|
|
gptkbp:relatedTo
|
gptkb:SqueezeNet
gptkb:EfficientNet
gptkb:ShuffleNet
|
|
gptkbp:successor
|
gptkb:MobileNetV2
gptkb:MobileNetV3
|
|
gptkbp:uses
|
depthwise separable convolutions
|
|
gptkbp:bfsParent
|
gptkb:convolutional_neural_network
|
|
gptkbp:bfsLayer
|
5
|