Tag Archives: CNN

Read paper “In-Datacenter Performance Analysis of a Tensor Processing Unit”

Paper reference: In-Datacenter Performance Analysis of a Tensor Processing Unit” Application Using floating point (16bit or 32bit) for NN (Neural Network) training, then a step called quantization transforms floating-point numbers into narrow integers–often just 8 bits–which are usually good enough for inference. MLP(Multi-layer Perceptions), CNN(Convolutional Neural Netowrks), and RNN(Recurrent Neural… Read more »

Use mxnet to classify images of birds (third episode)

After using CNN in previous article, it still can’t recognize the correct name of birds if the little creature stand on the corner (instead of the center) of the whole picture. Then I started to think about the problem: how to let neural-network ignore the position of the bird in… Read more »

Use mxnet to classify images of birds (second episode)

Using one convolutional-layer and two fully-connected-layers cost too much memory and also have bad performance for training, therefore I modify the model to two convolutional-layers and two narrow fully-connected-layers:

and training it by using learning rate “0.1” instead of “0.01” which may cause “overfit” in neural network. Finally, the… Read more »

Use mxnet to classify images of birds (first episode)

Recently, I was trying to classify images of birds by using machine learning technology. The most familiar deep learning library for me is the mxnet, so I use its python interface to build my Birds-Classification-System. For having not sufficient number of images for all kinds of bird, I just collect… Read more »