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.
Here is an overview of the
model:
EfficientNet is a family of convolutional neural networks and these models efficiently scale up in terms of layer depth, layer width, input resolution, or a combination of all of these factors. EfficientNet allows us to form features from images that can later be passed into a classifier. This allows for EfficientNet to serve as a backbone to many other models--one of which is EfficientDet, an object detection model family. This version of EfficientNEt is implemented in Keras, which is abstracted, so we can load a custom dataset and train EfficientNet all in a few lines of code.
EfficientNet is able to achieve higher accuracies and efficiencies all while reducing the parameter size and FLOPS.
Training EfficientNet: https://blog.roboflow.com/how-to-train-efficientnet/
YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.
YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.
YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.
YOLOv8 is here, setting a new standard for performance in object detection and image segmentation tasks. Roboflow has developed a library of resources to help you get started with YOLOv8, covering guides on how to train YOLOv8, how the model stacks up against v5 and v7, and more.
Roboflow offers a range of SDKs with which you can deploy your model to production.
EfficientNet
uses the
uses the
annotation format. If your annotation is in a different format, you can use Roboflow's annotation conversion tools to get your data into the right format.
You can automatically label a dataset using
EfficientNet
with help from Autodistill, an open source package for training computer vision models. You can label a folder of images automatically with only a few lines of code. Below, see our tutorials that demonstrate how to use
EfficientNet
to train a computer vision model.
Curious about how this model compares to others? Check out our model comparisons.
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