How do i go about to create and train a simple neural network in order to recognise patterns?
Does anybody have sample codes to guide me through or someone points to a direction?
Firstly you could start by reading the Neural Network Toolbos users guide. Also take a look at this tutorial. You have code samples so it is a good start. Good luck.
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What would be best way to detect difference between 2 images, one image is taken at beginning of process and the other at the end, goal is to detect if there is any difference in the images.
Based on my research neural networks seems good for this type of problem, but I don't have experience using them, I am not sure should this problem be treated as classification or anomaly detection? Also if you have any useful literature/GitHub projects/papers to share I would be thankful.
I have question about design of Neural Net.
I'm quite new to topic, but I have solid intuition about it.
I know I should use convolutional neural network for it.
But what existing design of net may I use?
I want to classify some object on picture, for instance road signs.
Where should I look?
Thank you!
Yes, fine-tuned convolutional neural network is a cutting edge architecture for such task.
Usually, CNN is composed of successive convolutional and pooling layers and has some fully-connected layers on the output.
I'd strongly recommend you to check out this link for detailed explanation.
CNN is OK.
I wouldn't use tensorflow. I suggest to look at the framework caffe. Sorry for my bad english.
Here is the link for Geoff Hinton's Matlab code.
He has made this code for handwriting recognition.
I want an object recognition code, so I want to train it with my own image. I am doing it by making few changes (loading my own image data-sets instead of digit0.mat) in makebatches.m file.
But I am not able to find after training it, that from where to test the created neural network in my own way?
Can someone please help by looking into the code?
I will take my graduation project next semester , I decide to complete my high degrees studying ,because I'm from low-income people , I want to dive on anything that helps me to do a paper or research or something supports my situation to gain scholarship.
my supervisor suggests that intrusion detection system using neural network is suitable for me , and he will help me , but I need to know fundamentals on this field .
there is limited resources on this topic , just thesis , papers and researches talk about only overview on IDs using neural network .
can anyone provides me some resources and references introduce me to
intrusion detection system using neural network to learn the fundamentals and basic ?
First, some background; Neural nets are by design black box. It is less important to understand the problem you are solving when designing a neural network than it is when writing a deterministic algorithm to solve it directly. With that in mind, you probably don't need to learn about "intrusion detection systems using neural networks", but would probably benefit more from learning about neural networks and intrusion systems separately.
I will leave it to you to find texts on intrusion detection systems, but would recommend reading the following to get started on what neural networks are, and how they work:
Neural Networks - A Systematic Introduction
If you think you have understood the basis of neural networks conceptually, you will want to learn a programming language. Your options diverge somewhat at this point, but I would suggest that if you want to learn neural nets from an academic perspective and want to have more control over the design and guts of the program, you would probably benefit most from learning C++. There is a wealth of knowledge on the topic of learning C++ online. In fact, probably the most popular page on this website is dedicated to that topic:
The Definitive C++ Book Guide and List
Once you understand neural network fundamentals and C++, the world is your oyster! If you're feeling adventurous, have a look at Kenneth Stanley's NEAT algorithm. The source code will teach you a lot about neural net algorithms.
From here to creating a learning machine that understands intrusion attempts is almost trivial from a programming perspective. You really just need to get the data, which may be really easy or really hard, but your supervisor should be able to help you find data sources on which to train the network once you reach this point.
Good luck!
Hey guys, Am wondering if anybody can help me with a starting point for the design of a Neural Network system that can recognize visual patterns, e.g. checked, and strippes. I have knowledge of the theory, but little practical knowledge. And net searches are give me an information overload. Can anybody recommend a good book or tutorial that is more focus on the practical side.
Thank you!
Are you only trying to recognize patterns such as checkerboards and stripes? Do you have to use a neural network system?
Basically, you want to define a bunch of simple features on the board and use them as input to the learning system. It can often be easier to define a lot of binary features and feed them into a single-layer network (what can become essentially linear regression).
Look at how neural networks were used for learning to play backgammon (http://www.research.ibm.com/massive/tdl.html), as this will help give you a sense of the types of features that make learning with a neural network work well.
As suggested above, you probably want to reduce your image a set of features. A corner detector (perhaps the Harris method) could be used to determine features in the checkerboard pattern. Likewise, an edge detector (perhaps Canny) could be used in the stripes case. As mentioned above, the Hough transform is a good line detection method.
MATLAB's image processing toolbox contains these methods, so you might try those for rapid prototyping. OpenCV is an open-source computer vision library that also provides these tools (and many others).