YOLO-World vs. EfficientNet: Compared and Contrasted

Models

YOLO-World

YOLO-World is a zero-shot object detection model.

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

Classification

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

CNN

Frameworks

Keras

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

2.9k+

License

GPL-3.0

Paper

Training Notebook

Deploy Model

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YOLO-World vs. EfficientNet

Both

YOLO-World

and

EfficientNet

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

YOLO-World

and

EfficientNet

	YOLO-World	EfficientNet
Date of Release	Jan 31, 2024	May 28, 2019
Model Type	Object Detection	Classification
Architecture	YOLO	CNN
GitHub Stars	2900	7200

YOLO-World

YOLO-World is a zero-shot object detection model.

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

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

Learn more about YOLO-World

Learn more about EfficientNet