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
Item 1 Info
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

Compare MobileNet V2 Classification vs. EfficientNet

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.