Models
EfficientNet vs. Scaled-YOLOv4

EfficientNet vs. Scaled-YOLOv4

Both EfficientNet and Scaled YOLOv4 are commonly used in computer vision projects. Below, we compare and contrast EfficientNet and Scaled YOLOv4.

Models

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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.
Learn more about EfficientNet
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Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.
Learn more about Scaled YOLOv4
Model Type
Classification
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
CNN
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YOLO
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Annotation Format
Instance Segmentation
Instance Segmentation
Framework
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Keras
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PyTorch
GitHub
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View Repo
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View Repo
GitHub Stars
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2k+
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License
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GPL-3.0
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Paper
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View Paper
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View Paper
Training Notebook
Train on Colab
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Train on Colab
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Deploy Model
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Deploy with Roboflow
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Deploy with Roboflow
Compare Alternatives
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Compare EfficientNet and Scaled YOLOv4 with Autodistill

Compare EfficientNet vs. Scaled-YOLOv4

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.