Artificial Intelligence with .NET

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Presentation transcript:

Artificial Intelligence with .NET Boian Mitov Artificial Intelligence with .NET Mitov Software mitov@mitov.com www.mitov.com

Types of Artificial Intelligence Expert systems (Early 80s) Planning engines Classifiers

Classifiers and feature extractors Features are extracted from the data The features are passed to classifier The classifier detects conditions based on the features Features Conditions Data Data extractor extractor classifier

Types of classifiers Neural networks (including Perceptron) Naïve(Normal) Bayes Hidden Markov model Kernel Methods Support vector machine k-nearest neighbor algorithm Mixture model (including Gaussian mixture model) Decision tree Linear Classifier Self Organizing Maps(including Growing self-organizing maps) Generative Topographic Maps

Types of training for classifiers Supervised training Non supervised training Self Organizing Classifiers

AI Classifier Applications SPAM filtering Computer vision OCR Speech recognition Diagnostic utilities Industrial control Investment Code formatting Gesture recognition Robotics Games Function approximation

Neural Networks Simulates the way the brain works. Consists of neurons. Feedforward or Recurrent. Usually uses backpropagation to train.

Feedforward Neural Network

Neuron (with Sigmoid function) X1 W1 F(u) W2 u y X2 + W3 X3

Recognizing images with AI The images can have different orientation and position Scanning technics are usually employed Rotating the image and passing it trough classifier may produce unexpected results It is better to train with rotated images

AI Training Challenges More relevant features result in better prediction The classifiers tend to require a lot of computing power Selecting a good training set is very important

Speeding up the classifiers Parallel execution on multiple CPUs Execute on GPU Distributed execution on multiple system Execute in FPGA

The business of AI There is a constant demand for better classifiers, and implementations of existing classifiers Training is intellectual property and a product of its own

About the Speaker Boian Mitov – President of Mitov Software mitov@mitov.com Mitov Software – www.mitov.com products: VideoLab – Video processing library AudioLab – Audio processing library SignalLab – Digital signal processing library VisionLab – Computer vision library PlotLab – Data visualization library InstrumentLab – Visual instrumentation library IntelligenceLab – Artificial intelligence library LogicLab – Boolean logic library AnimationLab – Universal animation library CommunicationLab – Serial and TCP/IP Communication library Visual Live Binding – Universal visual live binding library Mitov.Runtime – Free Delphi library OpenWire Studio – Graphical development environment for Windows Visuino – Graphical development environment for Arduino Free open source libraries maintained by Mitov Software: www.openwire.org – The OpenWire library www.igdiplus.org – The IGDI+ library ( Delphi friendly GDI+ library )