Models
MobileNet V2 Classification vs. EfficientNet

MobileNet V2 Classification vs. EfficientNet

Both MobileNet V2 Classification and EfficientNet are commonly used in computer vision projects. Below, we compare and contrast MobileNet V2 Classification and EfficientNet.

Models

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MobileNet V2 Classification

MobileNet is a GoogleAI model well-suited for on-device, real-time classification (distinct from MobileNetSSD, Single Shot Detector). This implementation leverages transfer learning from ImageNet to your dataset.
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EfficientNet

EfficientNet is from a family of image classification models from GoogleAI that train comparatively quickly on small amounts of data, making the most of limited datasets.
Model Type
Classification
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Classification
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Model Features
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Item 2 Info
Architecture
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CNN
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Frameworks
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Keras
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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License
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Training Notebook

Compare MobileNet V2 Classification and EfficientNet with Autodistill

Models

MobileNet V2 Classification vs. EfficientNet

.

Both

MobileNet V2 Classification

and

EfficientNet

are commonly used in computer vision projects. Below, we compare and contrast

MobileNet V2 Classification

and

EfficientNet
  MobileNet V2 Classification EfficientNet
Date of Release May 28, 2019
Model Type Classification Classification
Architecture CNN
GitHub Stars 7200

MobileNet V2 Classification

MobileNet is a GoogleAI model well-suited for on-device, real-time classification (distinct from MobileNetSSD, Single Shot Detector). This implementation leverages transfer learning from ImageNet to your dataset.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix

EfficientNet

EfficientNet is from a family of image classification models from GoogleAI that train comparatively quickly on small amounts of data, making the most of limited datasets.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix

Compare MobileNet V2 Classification to other models

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