Day 8: Using a pre-trained neural network to classify the Caltech-101 dataset

Today I began to experiment with using a pre-trained neural network in order to have a higher accuracy in testing. I used resnet-18 which is a neural net that has been trained on a data set with 14 million images. This allows resnet-18 to identify specific features like edges or corners. The detection of these edges is called feature identification and it is a large advantage of using a pre-trained neural network. Using resnet-18 also reduces training time because the network already has a good idea on how to tell apart images. I plan to test my pre-trained neural net on the caltech-101 data set later this week.





Source: http://web.eecs.umich.edu/~honglak/cacm2011-researchHighlights-convDBN.pdf

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