EfficientNet vs. YOLOR: Compared and Contrasted

Models

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

YOLOR

YOLOR (You Only Learn One Representation) is an object detection model that uses both implicit and explicit knowledge to make predictions.

Learn more about YOLOR

Model Type

Classification

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

CNN

CNN, YOLO

Frameworks

Keras

PyTorch

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

2k+

License

GPL-3.0

Paper

Training Notebook

Deploy Model

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EfficientNet vs. YOLOR

Both

EfficientNet

and

YOLOR

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

EfficientNet

and

YOLOR

	EfficientNet	YOLOR
Date of Release	May 28, 2019	May 10, 2021
Model Type	Classification	Object Detection
Architecture	CNN	CNN, YOLO
GitHub Stars	7200	2000

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.

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