Scaled-YOLOv4 vs. Faster R-CNN: Compared and Contrasted

Models

Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.

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.

Learn more about Faster R-CNN

Model Type

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

Frameworks

PyTorch

TensorFlow 1.5

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

2k+

7.5k+

License

GPL-3.0

MIT

Paper

Training Notebook

Deploy Model

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Scaled-YOLOv4 vs. Faster R-CNN

Both

Scaled YOLOv4

and

Faster R-CNN

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

Scaled YOLOv4

and

Faster R-CNN

	Scaled YOLOv4	Faster R-CNN
Date of Release
Model Type	Object Detection	Object Detection
Architecture	YOLO
GitHub Stars	2000	7500

Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

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.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

Learn more about Scaled YOLOv4

Learn more about Faster R-CNN