goingDeeperWithConvolutions: Difference between revisions
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= Introduction = | = Introduction = | ||
In the last three years, due to the advances of deep learning and more concretely convolutional networks, the quality of image recognition has increased dramatically. The error rates for ILSVRC competition | In the last three years, due to the advances of deep learning and more concretely convolutional networks, the quality of image recognition has increased dramatically. The error rates for ILSVRC competition dropped significantly year by year.[http://image-net.org/challenges/LSVRC/ LSVRC] This paper proposed a new deep convolutional neural network architecture codenamed Inception. With the inception module and carefully crafted design researchers build a 22 layers deep network called Google Lenet, which uses 12X fewer parameters while being significantly more accurate than the winners of ILSVRC 2012. [http://www.cs.toronto.edu/~fritz/absps/imagenet.pdf [1]] | ||
Revision as of 15:09, 20 October 2015
Introduction
In the last three years, due to the advances of deep learning and more concretely convolutional networks, the quality of image recognition has increased dramatically. The error rates for ILSVRC competition dropped significantly year by year.LSVRC This paper proposed a new deep convolutional neural network architecture codenamed Inception. With the inception module and carefully crafted design researchers build a 22 layers deep network called Google Lenet, which uses 12X fewer parameters while being significantly more accurate than the winners of ILSVRC 2012. [1]