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Neural Network Experiencing with different NN libraries By Manoj Katwal.

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Presentation on theme: "Neural Network Experiencing with different NN libraries By Manoj Katwal."— Presentation transcript:

1 Neural Network Experiencing with different NN libraries By Manoj Katwal

2 Outline Aforge Library BackProp Library Tiberius Data Mining Software BrainNetIntro Multi Layer Perceptron (demo exe) Neural Network Very Simple (source code)

3 Aforge Library Availability: Library to implement your own problem, Library Docs, and Sample source code implementing library What does it support? -- Neuro (NN our interest) -- Genetic Algorithm (for next HW) -- Image Processing (complex for now)

4 Contd…(Aforge Library) Walking through the source code Implementation easy? Example (demo)

5 Back Propagation NN A C++ class implementation Nicely explained Reference: http://www.codeproject.com/cpp/BP.asp http://www.codeproject.com/cpp/BP.asp

6 Tiberius Data Mining Soft. Software is available for download to use Need to get the license for the full features Academic license for Student High percentage of approval from users No programming knowledge required to use the software

7 Brain Net Source code is available for downlaod (FREE) In depth explanation Interesting example on “Developing An Image/Pattern Detection System” Lets take a look at the simple Image/Pattern detection demo Reference: http://www.codeproject.com/useritems/neuralnetw ork.asp http://www.codeproject.com/useritems/neuralnetw ork.asp

8 Multi Layer Perceptron No source code available Executable file is available to download

9 Neural Network Very Simple Source Code Very simple easy to understand source code for starters

10 Example: Automatic Eyeglass Removal An input face image. Face localization by Active Shape Model (ASM). Glasses recognition by a classifier. Glasses localization by Markov Chain Monte Carlo method (MCMC). Glasses removal by a set of training data.


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