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Google Inception V4

About Algorithm

Google Inception architecture is one of the top advances in image recognition performance achieved with relatively low computational cost. Inception-v4 neural network combines traditional network architecture with residual connections, which allowed to significantly accelerate the training and achieve state-of-the-art performance in 2015 ILSVRC challenge.

Inception-v4

Features

Module

TensorFlow

Top-1 Accuracy

80.6%

Top-5 Error

3.08%

Network Type

Deep convolutional network

Activation Function

ReLu

Number of Parameters

43 million

Optimizer

RMSprop (Decay 0.9)

Learning rate

0.045

Inception Code

GitHub Repository

Copyright 2016 The TensorFlow Authors. All Rights Reserved. Inception Creators: Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi

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