YOLOv10 vs. Faster R-CNN: Compared and Contrasted

Models

YOLOv10

YOLOv10 is a real-time object detection model introduced in the paper "YOLOv10: Real-Time End-to-End Object Detection".

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

7800

7.5k+

License

GNU Affero General Public

MIT

Paper

Training Notebook

Deploy Model



YOLOv10 vs. Faster R-CNN

Both

YOLOv10

and

Faster R-CNN

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

YOLOv10

and

Faster R-CNN

	YOLOv10	Faster R-CNN
Date of Release	May 23, 2024
Model Type	Object Detection	Object Detection
Architecture	YOLO
GitHub Stars	7800	7500

YOLOv10

YOLOv10 is a real-time object detection model introduced in the paper "YOLOv10: Real-Time End-to-End Object Detection".

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

https://blog.roboflow.com/what-is-yolov10/

Learn more about Faster R-CNN