YOLOv4 Tiny vs. EfficientNet

Both YOLOv4 Tiny and EfficientNet are commonly used in computer vision projects. Below, we compare and contrast YOLOv4 Tiny and EfficientNet.

Models

YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset

Learn more about YOLOv4 Tiny

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

ResNet-D, YOLO

CNN

Frameworks

Darknet

Keras

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

License

YOLO

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare YOLOv4 Tiny vs. EfficientNet

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.

YOLOv4 Tiny vs. EfficientNet

Models

YOLOv4 Tiny

EfficientNet

Compare YOLOv4 Tiny and EfficientNet with Autodistill

Compare YOLOv4 Tiny vs. EfficientNet