what activation function

Http://www.cnblogs.com/lc1217/p/7132364.html 1. About Keras 1) Introduction Keras is a theano/tensorflow-based, in-depth learning framework written by pure Python. Keras is a high level neural network API that supports fast experiments that can

Linear decoder Contents [hide] 1 sparse self-coding restatement 2 Linear Decoder 3 Chinese-English version of the sparse self-coding restatement The sparse Self encoder contains 3 layers of neurons, namely the input layer, the hidden layer and the

In addition to the weight attenuation described earlier, the deep learning model often uses the Discard method (dropout) to cope with overfitting problems.Methods and principlesTo ensure the certainty of the test model, the use of the Discard method

Overview Hardware on the use of stm32f4+mpu9150 implementation of the neural network recognition gesture, but not with the IMU geomagnetic data, only with the three-axis accelerometer and three-axis gyroscope data, the board is the main reference

This section mainly introduces a deep learning MATLAB version of the Toolbox, Deeplearntoolbox The code in the Toolbox is simple and feels more suitable for learning algorithms. There are common network structures, including deep networks (NN),

Deep learning over the past few years, the feature extraction capability of convolutional neural Networks has made this algorithm fire again, in fact, many years ago, but because of the computational complexity of deep learning problems, has not

The inverse propagation algorithm is an important algorithm in the training of multilayer neural networks, and the principle and derivation process of directional propagation algorithm are emphatically explained in this paper. Therefore, for some

PrefaceNumber third is going to attend the CAD/CG conference and cast a paper on the use of generation models and discriminant models to do motion capture data style recognition. This period of time has been engaged in convolution RBM, almost the

Since cross-domain file transmission is recently underway, SQL broker is used for a brief introduction, most of which are from msdn. Service broker is a new technology in Microsoft SQL Server 2005 that helps database developers generate secure,

One of the major features of YOLO is that it is fast and can be completely real-time in processing. The reason is that the whole detection method is very concise, using regression method, directly in the original image of the target detection and

In the previous article, we saw how neural networks use gradient descent algorithms to learn their weights and biases. However, we still have some explanations: we did not discuss how to calculate the gradient of the loss function. This article will

Reference booksDeep learningDeep learning is a new field in machine learning research, and its motive is to establish and simulate the neural network of human brain import analysis and learning, which imitates the mechanism of human brain to

What I-READ for deep-learningToday, I spent some time on the new papers proposing a new from training very deep neural networks (Highway-networks) an d A new activation function for auto-encoders (Zero-bias autoencoders and the benefits

These two days in the study of artificial neural networks, using the traditional neural network structure made a small project to identify handwritten numbers as practiced hand. A bit of harvest and thinking, want to share with you, welcome advice,

Review of AI in game development(Personal review, some are only to their own review tips (=w=), reproduced annotated Source: http://blog.csdn.net/hcbbt/article/details/42815479)Supporting materials: Artificial Intelligence in game development

Previous 4ArticleThis is a fuzzy system, which is different from the traditional value logic. The theoretical basis is fuzzy mathematics, so some friends are confused. If you are interested, please refer to relevant books, I recommend the "fuzzy

I want to write a series of deep learning simple practical tutorials, using mxnet to do the implementation of the platform of the example code to explain the deep learning commonly used in some technical direction and practical examples. The main

Deep learning over the past few years, the feature extraction capability of convolutional neural Networks has made this algorithm fire again, in fact, many years ago, but because of the computational complexity of deep learning problems, has not

#http://python.jobbole.com/82758/#import NumPy as NP#### sigmoid function#def nonlin (x, deriv=false):#if (Deriv = = True):#return x * (1-x)#return 1/(1 + np.exp (-X))#### Input DataSet#X = Np.array ([[0, 0, 1],#[0, 1, 1],#[1, 0, 1],#[1, 1, 1]])###

Datasets:Labelme:consists of hundreds of thousands of fully-segmented imagesImagenet:consists of over million labeled high-resolution images in over 22000 categoriesThe data set used in this paper is imagenetSuperfluous words:The imagenet contains