keras convolutional neural network

ExplainThis allows us to learn to predict a person ' s identity using a Softmax output unit, where the number of classes equals the Number of persons in the database plus 1 (for the final "not in Database" Class).Reasons for the above options error:1, plus 1 explanation error:Put someone's photo into the convolutional neural network, use the Softmax unit to outpu

convolution kernel shares an offset, which is no doubt, but does the multiple convolution cores share a bias?] No, a convolution kernel shares a bias item]Four. CNN Example LeNet-5LeNet-5 is a typical convolutional neural network used to identify numbers, which has a total of 7 layers. As shown below: http://yann.lecun.com/exdb/lenet/index.html.Figure 3 LeNet-5I

convolutional Neural NetworksReprint Please specify: http://blog.csdn.net/stdcoutzyx/article/details/41596663Since July this year, has been in the laboratory responsible for convolutional neural networks (convolutional neural

convolutional Neural NetworksReprinted from: http://blog.csdn.net/stdcoutzyx/article/details/41596663Since July this year, has been in the laboratory responsible for convolutional neural networks (convolutional neural

Recently has been looking at convolutional neural network, want to improve the improvement to make something new, read a lot of papers, wrote a review of Deep learning convolutional neural Network has some new understanding, and s

, also representing the highest level of convolutional neural networks, as well as the default choice for practice (May 2016). Densenet (August 2016): Published by Gao Huang, each layer of densely Connected convolutional network is directly connected to the other layers in front of each other. Densenet has shown remark

"Recurrent convolutional neural Networks for Text classification" Paper Source: Lai, S., Xu, L., Liu, K., Zhao, J. (2015, January). Recurrent convolutional neural Networks for Text classification. In Aaai (vol. 333, pp. 2267-2273). Original link: http://blog.csdn.net/rxt2012kc/article/details/73742362 1. Abstract Te

Keras is a Theano and TensorFlow-compatible neural network Premium package that uses him to component a neural network more quickly, and several statements are done. and a wide range of compatibility allows Keras to run unhindered

"Convolutional neural Networks-evolutionary history" from Lenet to Alexnet This blog is "convolutional neural network-evolutionary history" of the first part of "from Lenet to Alexnet" If you want to reprint, please attach this article link: http://blog.csdn.net

convolutional neural Network Origin: The human visual cortex of the MeowIn the 1958, a group of wonderful neuroscientists inserted electrodes into the brains of the cats to observe the activity of the visual cortex. and infer that the biological vision system starts from a small part of the object,After layers of abstraction, it is finally put together into a pro

Read the Web page found that to learn deep learning, should be first on convolutional neural network (convolutional neural Networks, referred to as CNN), convolutional Neural

low)Going deeper Through the Network　　A Classic CNN Architecture would look like this:ReLU, Conv, ReLU, ReLU, Conv, ReLU, pool, Fully, Conv, CTED Layer(ReLU: Activation function, pool: pooling layer)There ' re other layers that is interspersed ( embellishment, scatter ) between these conv layers, they provide nonlinearities (ReLU) and preservation ( Dimension protection ) of dimension (Pool) that help to improve the robustness ( robustness ) of the

. The C5 is still labeled as a convolutional layer rather than a fully-connected layer, because if the input of LeNet-5 is larger and the others remain the same, then the dimension of the feature map will be larger than 1*1. The C5 layer has 48,120 training connections.The F6 layer has 84 units (The reason why this number is chosen is from the design of the output layer) and is fully connected to the C5 layer. There are 10,164 parameters that can be t

Weight sharing the word was first introduced by the LENET5 model, in 1998, LeCun released the Lenet network architecture, which is the following:Although most of the talk now is that the 2012 Alexnet network is the beginning of deep learning, the beginning of CNN can be traced back to the LENET5 model, and its features are widely used in the study of convolutional