EfficientNet vs. YOLOv4 Tiny

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

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

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

Model Type

Classification

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

CNN

ResNet-D, YOLO

Frameworks

Keras

Darknet

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 EfficientNet vs. YOLOv4 Tiny

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.

EfficientNet vs. YOLOv4 Tiny

Models

EfficientNet

YOLOv4 Tiny

Compare EfficientNet and YOLOv4 Tiny with Autodistill

Compare EfficientNet vs. YOLOv4 Tiny