deep learning mlp

Deep Learning, also known as unsupervised feature learning or feature learning, is a hot topic at present. This article mainly introduces the basic idea and common methods of deep learning. 1. What is

21. Application of Depth neural network in visual significance (visual Attention with deep neural Networks) (English, conference papers, 2015, IEEE Search)This article focuses on the application of CNN in the field of significance detection.　　22. Progress in deep learning Research (Chinese, Journal, 2015, net)A summary article on

The recent deep learning fire not only attracted the attention of the academic community, but also sought after in the industry. In many important evaluations, DL has achieved the effect of state of the art. Especially in terms of speech recognition, DL has reduced the error rate by about 30% and has made significant progress. If the company that uses speech recognition does not use DL, I am sorry to say he

A summaryIn this paper, we present a very simple image classification deep learning framework, which relies on several basic data processing methods: 1) Cascade principal component Analysis (PCA), 2) Two value hash coding, 3) chunking histogram. In the proposed framework, the multi-layer filter kernel is first studied by PCA method, and then sampled and encoded using two-valued hash coding and block histogr

probability, the probability that the return type is Softmax, and which highest result is evaluated. If you do a global system assessment, you can then add a layer of accuracy layer, the return type is accuracy. 3.2 2014 googlenet 2014 Imagenet Classification Detection Champion, 22-tier network ... To kneel, interested students to see the structure of the paper, where I can not cut off the screenshot ... In addition, give a few references: 1. Beginners to play: You can use the online convne

Deep learning with STRUCTURECharlie Tang is a PhD student in the machine learning group at the University of Toronto, working with Geoffrey Hinton andRuslan Salakhutdinov, whose the interests include machine learning, computer vision and cognitive science. More specifically, he had developed various higher-order extens

Recommended 10 open-source deep learning frameworks on GitHubRecently, Google Open source TensorFlow (GitHub), the move in the field of deep learning impact, because Google in the field of artificial intelligence research achievements, has a strong talent pool, and Google's own Gmail and search engines are using a self

Mobileye and Nvidia use a convnet based approach in their upcoming automotive Vision systems. Other increasingly important applications relate to natural language understanding and speech recognition. Despite these achievements, Convnets was largely abandoned by the mainstream computer vision and machine learning community until the Imagenet race in 2012. When the deep convolution network was applied to da

Time of instruction:This course will begin on April 1. The duration of the course is approximately 14 weeks. Subject:People who are interested in deep learning AI, who want to learn about deep learning practices. learners need a little bit of the basics of Python development and de