EfficientNet
EfficientNet: Rethinking Model Scaling for Convolutional Neural ...
We propose a new scaling method that uniformly scales all dimensions of depth/width/resolution using a simple yet highly effective compound coefficient.
EfficientNet Explained | Papers With Code
EfficientNet is a convolutional neural network architecture and scaling method that uniformly scales all dimensions of depth/width/resolution using a ...
Understanding EfficientNet — The most powerful CNN architecture
EfficientNet is based on the baseline network developed by the neural architecture search using the AutoML MNAS framework. The network is fine- ...
What is EfficientNet? The Ultimate Guide. - Roboflow Blog
What is EfficientNet? EfficientNet is a convolutional neural network built upon a concept called "compound scaling.” This concept addresses the ...
lukemelas/EfficientNet-PyTorch - GitHub
This repository contains an op-for-op PyTorch reimplementation of EfficientNet, along with pre-trained models and examples.
EfficientNet: Rethinking Model Scaling for Convolutional Neural ...
ImageNet Accuracy. All numbers are for single-crop, single-model. Our EfficientNets significantly out- perform other ConvNets. In particular, EfficientNet- ...
EfficientNet B0 to B7 - Keras Applications
This function returns a Keras image classification model, optionally loaded with weights pre-trained on ImageNet.
EfficientNet — Torchvision 0.18 documentation - PyTorch
The following model builders can be used to instantiate an EfficientNet model, with or without pre-trained weights. All the model builders internally rely on ...
EfficientNet: Optimizing Deep Learning Efficiency - viso.ai
What is EfficientNet? EfficientNet proposes a simple and highly effective compound scaling method, which enables it to easily scale up a ...
EfficientNet: Improving Accuracy and Efficiency through AutoML and ...
We propose a novel model scaling method that uses a simple yet highly effective compound coefficient to scale up CNNs in a more structured manner.
EfficientNet: The Definition, Use Case, and Relevance for Enterprises
How does it work? · EfficientNet achieves state-of-the-art performance on various image recognition tasks with fewer parameters and FLOPS compared to other CNN ...
The EfficientNet model was proposed in EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks by Mingxing Tan and Quoc V. Le. EfficientNets ...
EfficientNet. By NVIDIA. EfficientNets are a family of image classification models, which achieve state-of-the-art accuracy, being an order-of-magnitude smaller ...
Unlike conventional practice that arbitrary scales these factors, the EfficientNet scaling method uniformly scales network width, depth, and resolution with a ...
EfficientNet is a convolutional neural network architecture and scaling method that uniformly scales all dimensions of depth/width/resolution using a ...
EfficientNetV2: Smaller Models and Faster Training - arXiv
This paper introduces EfficientNetV2, a new family of convolutional networks that have faster training speed and better parameter efficiency than previous ...
EfficientNet: Rethinking Model Scaling for Convolutional Neural ...
In this story, EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (EfficientNet), by Google Research, Brain Team, is presented.
EfficientNet - Aman Arora's Blog
EfficientNet-B7 achieves state- of-the-art 84.4% top-1 / 97.1% top-5 accuracy on ImageNet, while being 8.4x smaller and 6.1x faster on inference than the best ...
What is EfficientNet? - Sky Engine AI
EfficientNet is a convolutional neural network that is based on the notion of "compound scaling." This idea tackles the age-old trade-off ...
efficientnet-widese-b4 weights (PyTorch, AMP, ImageNet) | NVIDIA ...
This model is trained with mixed precision using Tensor Cores on Volta and the NVIDIA Ampere GPU architectures.