在准确率上,EfficientNet 只比之前的 SOTA 模型 GPipe 提高了 0.1%,为了达到这个准确率 GPipe 用了 556M 参数而 EfficientNet 只用了 66M,恐怖如斯! 在实际使用中这 0.1% 的准确率我们可能压根感受不到,但是速度的提升确是实打实的,8 倍的速度提升大大提高了网络的 ... Ever since Alex net won the 2012 ImageNet Challenge, Convolutional Neural Networks have become ubiquitous in the world of Designing a simple mobile-size baseline architecture: EfficientNet-B0.Последние твиты от EFFICIENT (@efficientnet). Somos uma empresa de desenvolvimento de software, home pages e assessoria em tecnologia da informação.

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Unfortunately, the EfficientNet family of models is not eligible for fine-tuning for this experimental configuration. The below code-listing provides a utility function that downloads the respective feature extraction model, adds a classification top, compiles the final model, and finally returns it.

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May 29, 2019 · Model Size vs. Accuracy Comparison. EfficientNet-B0 is the baseline network developed by AutoML MNAS, while Efficient-B1 to B7 are obtained by scaling up the baseline network. In particular, our EfficientNet-B7 achieves new state-of-the-art 84.4% top-1 / 97.1% top-5 accuracy, while being 8.4x smaller than the best existing CNN. - An all-in-one solution for adding recessed downlighting to hospitality, retail, office and other commercial lighting applications

tensorflow libtensorflow/libtensorflow_jni-cpu-darwin-x86_64-1.9.0-rc1.tar.gz true images/sha256:000e84670eae7c89d25981cf9497158b77ff2d69bc7e3eeb290f4f88329aab64 ... There are a variety of convolutional neural networks and all have their own advantage. With the varying architectures, these models have shown an overwhelming performance in a number of computer...

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