://dev.openwrt.org.cn/wiki/branchstatThere are currently three branches,
1. Dreambox, based on openwrt 10.03.1,
2. SUN branch: The Branch optimized for the embedded platform of ARM architecture. It is created based on the Dreambox branch and maintained by Richard Nee.
3. pandorabox branch, based on OpenWrt 12.09.
1. Obtain the OpenWrt-Dreambox stable version:$ Sv
DreamBox is a linux-driven series of DVB satellites, ground and Cable Digital TV receivers (set-top boxes ). DreamBox has the Arbitrary File Download Vulnerability, which may cause leakage of sensitive information.
[+] Info:~~~~~~~~~DreamBox DM500 (+) Arbitrary File Download Vulnerability
[+] Poc:~~~~~~~~~Http: // 192.168.1.102/% 2f .. % 2f .. % 2f .. % 2f .. %
mount# option Target/home This line should not matter, I generally remove or add a "#" in frontOption DEVICE/DEV/SDA1Option Fstype ext3Option Options Rw,syncoption enabled 1Option Is_rootfs 1Config swapOption Device/dev/sda2Option enabled 0The red font is a modified or added content.Add the logo to identify whether to boot from the USB stick;Vi/mnt/etc/bannerAdded on last line: Boot from UpanAfter starting again, the effect is as follows:Connecting to 192.168.1.1:22 ...Connection established.To
Drawing a learning curve is useful, for example, if you want to check your learning algorithm and run normally. Or you want to improve the performance or effect of the algorithm. Then the learning curve is a good tool. The learning curve can judge a learning algorithm, which
Objective
Machine learning is divided into: supervised learning, unsupervised learning, semi-supervised learning (can also be used Hinton said reinforcement learning) and so on.
Here, the main understanding of supervision and unsupervised
[Introduction to machine learning] Li Hongyi Machine Learning notes-9 ("Hello World" of deep learning; exploring deep learning)
PDF
Video
Keras
Example application-handwriting Digit recognition
Step 1:define A set of function
Step 2:goodness of function
Step 3:pick the best function
X_t
Earlier, we mentioned supervised learning, which corresponds to non-supervised learning in machine learning. The problem with unsupervised learning is that in untagged data, you try to find a hidden structure. Because the examples provided to learners arenot marked, so there is no error or reward signal to evaluate the
As we all know, when Alphago defeated the world go champion Li Shishi, the whole industry is excited, more and more scholars realize that reinforcement learning is a very exciting in the field of artificial intelligence. Here I will share my intensive learning and learning notes. The basic concept of reinforcement learning
In machine learning, supervised learning (supervised learning) by defining a model and estimating the optimal parameters based on the data on the training set. The gradient descent method (Gradient descent) is a parametric optimization algorithm widely used to minimize model errors. The gradient descent method uses multiple iterations and minimizes the cost funct
Deep Learning notes finishing (very good)
Http://www.sigvc.org/bbs/thread-2187-1-3.html
Affirmation: This article is not the author original, reproduced from: http://www.sigvc.org/bbs/thread-2187-1-3.html
4.2, the primary (shallow layer) feature representation
Since the pixel-level feature indicates that the method has no effect, then what kind of representation is useful.
Around 1995, Bruno Olshausen and David Field two scholars, Cornell Unive
For the performance of four different algorithms in different size data, it can be seen that with the increase of data volume, the performance of the algorithm tends to be close. That is, no matter how bad the algorithm, the amount of data is very large, the algorithm can perform well.When the amount of data is large, the learning algorithm behaves better:Using a larger set of training (which means that it is impossible to fit), the variance will be l
supervised learning : In short, given a certain training sample (it is important to note that the sample is both data and data corresponding to the results), using this sample training to get a model (can be said to be a function), and then use this model to map all the input to the corresponding output, The output is then simply judged so that the problem of classification (or regression) is achieved. Simply make a distinction, the classification is
Transferred from: http://blog.csdn.net/zouxy09/article/details/8775518
Well, to this step, finally can talk to deep learning. Above we talk about why there are deep learning (let the machine automatically learn good features, and eliminate the manual selection process. As well as a hierarchical visual processing system for reference people, we get a conclusion that deep
Original address: http://www.cnblogs.com/cyruszhu/p/5496913.htmlDo not use for commercial use without permission! For related requests, please contact the author: [Email protected]Reproduced please attach the original link, thank you.1 BasicsL Andrew NG's machine learning video.Connection: homepage, material.L 2.2008-year Andrew Ng CS229 machine LearningOf course, the basic method does not change much, so the courseware PDF downloadable is the advanta
I don't know. As a complete Windows platform under the less professional software engineering students, see the "Accelerated C + +" source code, the first reaction is: Oh! I should use make to generate project files. Then I happily use AOL to start searching for relevant information.And then the egg! I must have been possessed by some strange creature. I should import files directly with VS Create Project. Then ... ctrl+f5. How perfect.But...... Following:"Tutorial" from the cloud-wind Big blog
IntroductionThe systematic learning machine learning course has benefited me a lot, and I think it is necessary to understand some basic problems, such as the category of machine learning algorithms.Why do you say that? I admit that, as a beginner, may not be in the early stage of a learning object has a comprehensive
Deep Learning (depth learning) Learning notes finishing Series[Email protected]Http://blog.csdn.net/zouxy09ZouxyVersion 1.0 2013-04-08Statement:1) The Deep Learning Learning Series is a collection of information from the online very big Daniel and the machine
URL can be used as the file name. For more information on how to specify filenames see fopen (). Different features of various wapper see supported protocols and encapsulation protocols, and note their usage and the predefined variables available.
URL meaning is not can choose a non-GD2 format picture, but I tried not
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sixth week. Design of learning curve and machine learning system
Learning Curve and machine learning System Design
Key Words
Learning curve, deviation variance diagnosis method, error analysis, numerical evaluation of machine learning
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