Models
Scaled-YOLOv4 vs. EfficientNet

Scaled-YOLOv4 vs. EfficientNet

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

Models

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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
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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
Model Type
Object Detection
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Classification
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
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CNN
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Annotation Format
Instance Segmentation
Instance Segmentation
Framework
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PyTorch
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Keras
GitHub
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View Repo
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View Repo
GitHub Stars
2k+
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License
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
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Compare Scaled YOLOv4 and EfficientNet with Autodistill

Compare Scaled-YOLOv4 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.