Models
EfficientNet vs. Faster R-CNN

EfficientNet vs. Faster R-CNN

Both EfficientNet and Faster R-CNN are commonly used in computer vision projects. Below, we compare and contrast EfficientNet and Faster R-CNN.

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.
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Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server.
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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Frameworks
Keras
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TensorFlow 1.5
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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7.5k+
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License
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MIT
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Training Notebook

Compare EfficientNet and Faster R-CNN with Autodistill

Compare EfficientNet vs. Faster R-CNN

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.