Original URL: http://www.iteye.com/news/312701. We should see deeper models, which can be learned from fewer training samples compared to today's models, and will make substantial progress in unsupervised learning. We should see more accurate and useful speech and visual recognition systems.2. I expect deep learning to be increasingly used for multi-mode (multi-m
About TensorFlow a very good article, reprinted from the "TensorFlow deep learning, an article is enough" click to open the link
Google is not only the leader in big data and cloud computing, but also has a good practice and accumulation in machine learning and deep learning
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
Deep learning new Journey (1) [Email protected]http://www.cnblogs.com/swje/Zhouw2015-11-26Statement:1) The Deep Learning Learning Series is a collection of information from the online very big Daniel and the machine learning exper
In view of my knowledge of machine learning and statistics, insufficient, temporarily do not translate. I just write down the original English, there may be mistakes, quite fun. Also saw a piece of Chinese article, found in the video recorded in the Deep learning development of the time point.
First, record the difference between
Learning notes TF042: TF. Learn, distributed Estimator, deep learning Estimator, tf042estimator
TF. Learn, an important module of TensorFlow, various types of deep learning and popular machine learning algorithms. TensorFlow offic
Reprint: Https://mp.weixin.qq.com/s/J6eo4MRQY7jLo7P-b3nvJg
Li Lin compiled from PyimagesearchAuthor Adrian rosebrockQuantum bit Report | Public number Qbitai
OpenCV is a 2000 release of the open-source computer vision Library, with object recognition, image segmentation, face recognition, motion recognition and other functions, can be run on Linux, Windows, Android, Mac OS and other operating systems, with lightweight, efficient known, and provides multiple language interfaces.
OPENCV's latest
First, prefaceAs deep learning continues to evolve in areas such as image, language, and ad-click Estimation, many teams are exploring the practice and application of deep learning techniques at the business level. And in the Advertisement Ctr forecast aspect, the new model also emerges endlessly: Wide and
Deep learning is one of the most important research directions for us, and it is also a necessary tool for the industry to realize a lot of amazing functions and the path to artificial intelligence.Let's take a look at what deep learning can do, the drone of Google research, whose components are made up of two parts, o
The topic of this class is deep learning, the person thought to say with deep learning relatively shallow, with Autoencoder and PCA this piece of content is relatively close.Lin introduced deep learning in recent years has been a
-ser Ies-based Anomaly DetectIon algorithms AI Class Introduction search algorithms A-star heuristic search Constraint satisfaction algorithms with AP Plications in computer Vision and scheduling Robot Motion planning hillclimbing, simulated annealing and genetic algorithm S 2.
Stanford University opened a course on "deep learning and natural language processing" in March: Cs224d:deep
UFLDL tutorialfrom ufldl Jump to:navigation, search
Description: This tutorial would teach you the main ideas of unsupervised Feature learning and deep learning. By working through it, you'll also get to implement several feature learning/deep
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