yolo deep learning

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

, such as the right half, should be added.Unefficient Grid Size reductionThere is a problem, it will increase the computational capacity, so szegedy came up with the following pooling layer.Efficient Grid Size reductionAs you can see, Szegedy uses two parallel structures to complete the grid size reduction, respectively, the right half of the conv and pool. The left half is the inner structure of the right part.Why did you do this? I mean, how is this structure designed? Szegedy no mention, perh

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

7.27 after the summer vacation, I started to run the deep learning program after I completed the financial project. Hinton ran the article code on nature for three days, and then DEBUG changed the batch from 200 to 20. Later, I started reading articles and felt dizzy. It turns to: Deep Learning tutorials installs thean

The Wunda "Deep learning engineer" Special course includes the following five courses: 1, neural network and deep learning;2, improve the deep neural network: Super parameter debugging, regularization and optimization;3. Structured machine

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

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

Source: http://www.teglor.com/b/deep-learning-libraries-language-cm569Python Theano is a Python library for defining and evaluating mathematical expressions with numerical arrays. It makes it easy-to-write deep learning algorithms in Python. The top of the Theano many more libraries is built. kerasis

The application of deep learning in the ranking of recommended platform for American group reviewsOriginal address: https://tech.meituan.com/dl.htmlPan Hui Group reviews search for recommended teams · 2017-07-28 14:33 United States as the largest domestic service platform, business types involved in food, live, line, play, music and other fields, is committed to let everyone eat better, live better, there

Deep Learning (3) Analysis of a single-layer unsupervised learning network Zouxy09@qq.com Http://blog.csdn.net/zouxy09 I have read some papers at ordinary times, but I always feel that I will slowly forget it after reading it. I did not seem to have read it again one day. So I want to sum up some useful knowledge points in my thesis. On the one hand, my understa

) , you can also follow one of the best courses onmachine learning course from Yaser Abu-mostafa. If you need more lucid explanation for the techniques, you can opt for Themachine learning course from Andrew Ng and follow The exercises on Python. tutorials (Individual guidance) On Scikit Learn Assignment: Try out this challenge on KaggleStep 7:practice, practice and practiceCongratulations,

0. OriginalDeep learning algorithms with applications to Video Analytics for A Smart city:a Survey1. Target DetectionThe goal of target detection is to pinpoint the location of the target in the image. Many work with deep learning algorithms has been proposed. We review the following representative work:SZEGEDY[28] modified the

been fitted, you are combining these predictions in a simple way (average, weighted average, logistic regression), and then there is no space for fitting. Unsupervised learning8) Clustering algorithm Clustering algorithm is to process a bunch of data, according to their similarity to the data clustering .Clustering, like regression, is sometimes described as a kind of problem, sometimes describing a class of algorithms. Clustering algorithms typically merge input data by either a central p

difficult to benefit from end-to-end learning methods; The DCF algorithm is less than two: Model updating adopts the method of sliding weighted averaging, which is not the optimal updating method, because once the noise is involved in the update, it is likely to lead to the drift of the model, so it is difficult to simultaneously get the stability and adaptability of the model. Improvement One: The model of DCF algorithm is regarded as convolution fi

July algorithm December machine learning online Class---20th lesson notes---deep learning--rnnJuly algorithm (julyedu.com) December machine Learning Online class study note http://www.julyedu.com Cyclic neural networks Before reviewing the knowledge points:Fully connected forward network:

Some of the material of the deep learning introductory study are summarized according to the answers of some of Daniel's replies:Be noted that SOME VIDEOS is on youtube! I believe that you KNOW how to ACESS them.1. Andrew Ng's machine learning contents of the first four chapters (linear regression and logistic regression)Http://open.163.com/special/opencourse/mac

similar to the dimensionality reduction) method. Maximum pooling divides the input image into overlapping image matrix blocks, and each sub-region outputs its maximum value. The two reasons why the maximum pooling method is very effective in the visual processing problem are:(1) Reduce the computational complexity of the upper level by reducing the non-maximum value.(2) The result of pooling supports translation invariance. In the convolution layer, each pixel point has 8 orientations that can

1.1 machine learning basics-python deep machine learning, 1.1-python Refer to instructor Peng Liang's video tutorial: reprinted, please indicate the source and original instructor Peng Liang Video tutorial: http://pan.baidu.com/s/1kVNe5EJ 1. course Introduction 2. Machine Learning (ML) 2.1 concept: involves multiple

Python implementation of multilayer neural networks. The code is pasted first, the programming thing is not explained. Basic theory reference Next: Deep Learning Learning Notes (iii): Derivation of neural network reverse propagation algorithm Supervisedlearningmodel, Nnlayer, and softmaxregression that appear in your code, refer to the previous note:

Free and open source mobile deep The learning framework, deploying by Baidu. This is the simply deploying CNN on mobile devices with the low complexity and the high speed. It supports calculation on the IOS GPU, and is already adopted by the Baidu APP. size:340k+ (on ARM v7)Speed:40ms (for IOS Metal GPU mobilenet) or MS (for Squeezenet)Baidu Research and development of the mobile end of the