tensorflow convolutional neural network

Case code: #建立抽象模型x = Tf.placeholder (Tf.float32, [None, 784])y = Tf.placeholder (Tf.float32, [None, ten]) #实际分布的概率值w = tf. Variable (Tf.zeros ([784, 10])b = tf. Variable (Tf.zeros (10))A = Tf.nn.softmax (Tf.matmul (x, W) + b) #基于softmax多分类得到的预测概率#定义损失函数和训练方法Cross_entropy = Tf.reduce_mean (-tf.reduce_sum (Y * tf.log (a), reduction_indices=[1])) #交叉熵Optimizer = Tf.train.GradientDescentOptimizer (0.5) #梯度下降优化算法, learning step is 0.5Train = Optimizer.minimize (cross_entropy) #训练目标: Minimizing loss

First, prefaceThis convolutional neural network is the further depth of the multilayer neural network described above, which introduces the idea of deep learning into the neural network

convolutional Neural Network (convolutional neural networks/cnn/convnets)Convolutional neural networks are very similar to normal neural net

Learning Goals Understand multiple foundational papers of convolutional neural networks Analyze the dimensionality reduction of a volume in a very deep network Understand and Implement a residual network Build a deep neural

It 's written in front . This paper introduces the task of identifying handwritten characters by using convolution neural network based on TensorFlow on Mnist dataset, including: {Two layers of volume base}+{a layer of Relu full link layer}+{the full link layer of Softmax layer}. Because the structure is simple, the code is clear, the whole article to the main c

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

mobilenets:efficient convolutional neural Networks for Mobile Vision applicationspaper Link:https://arxiv.org/pdf/1704.04861.pdf Abstract and prior work is a little, lazy. 1. Introductionintroduces an efficient network architecture and two hyper-parameters to build a very small, low latency (fast) model that can easily match the design requirements of mobile and

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

"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