Intelligent Systems - University of Groningen
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Intelligent Systems Nicolai Petkov, Michael Biehl en Michael H. F. Wilkinson Intelligent Systems Group June 9, 2006 MSc variant Intelligent Systems
Transcript of Intelligent Systems - University of Groningen
Intelligent Systems
Nicolai Petkov, Michael Biehl en Michael H. F. Wilkinson
Intelligent Systems Group
June 9, 2006
MSc variant Intelligent Systems
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The Intelligent Systems MSc variant
The Intelligent Systems variant focuses on modelling intelligence and onresearch into and development of highly autonomous automated systems whichcan perform complex “real-world” tasks.
The Intelligent Systems variant is a collaboration between
Computing science, research groups Intelligent Systems and FundamentalComputing Science (Faculty of Science)
Artifical Intelligence (Faculty of Social Sciences)
“Informatiekunde” (Faculty of Arts).
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Courses
The mandatory course in the Intelligent Systems variant are
Automated Reasoning
Computer Vision
Machine Learning
Multi-Agent Systems
Neural Networks
Pattern Recognition
Student Colloquium
Besides these courses a large amount of time is set aside for research projectswithin the Intelligent Systems research group. Finally there are subsidiarysubjects such as Natural Language Processing.
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Master’s Thesis Options
The master’s thesis research can be done in one of the following ways:
By participating in current research at the institute.
By doing research at companies involved in Intelligent Systems research
Abroad, through the Socrates programme for the exchange of students with:
prof. E. Alegre, Univ. of Leon, Spaindr. P. Campisi and prof A. Neri, University of Rome III, Italyprof. W. Kropatsch and dr. M. Kampel, TU Vienna, Austriaprof. M. Vento, University of Salerno, Italy.
Further collaboration:
prof. B.S. Manjunath, University of California at Santa Barbaradr L. Najman in Paris: a collaboration is being set up.prof. dr. B. Hammer, TU Clausthal/Germany, a collaboration is being set up
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Job Perspectives
The IS-variant is mainly aimed at research, either at universities (after a PhD) orin business. Some examples:
Medical imaging (Pie Medical, Philips Medical Systems)
Imaging, copying and printing (OCE)
Surveilance, sensing (Thales, Dacolian)
Multi-media and games
Content-based image retrieval (Google)
Astronomy (Astron)
Just in the north of the Netherlands, there are more than 20 companies andinstitutes involved in computer vision (now organizing themselves in theCluster Computer Vision Noord Nederland).
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Research
The main focus of research is on Computer Vision and Neural Networks andother learning systems. Recent and current projects are on:
Contour detection
Shape analysis
Texture analysis
Mathematical morphology
Design of fast algorithms
Research into neural networks from a statistical physics perspective.
Application of machine learning in bioinformatics
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Example I
Cluttered scene Edge detector Contour detector
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Example II
Complex scene Detection of traffic sign
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Example III
Query object Retrieval result
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Example IV
Newly developed connected shape filters filter out noise without suppressinglarge aneurism, unlike standard filters.
3D Angiogram Standard filter Connected filter
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Example V
The filters improve automatic segmentation results
Angiogram Connected filter result
Segmented angiogram Segmented filtered volume
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Example VI
Training of Neural Networks
input data e.g
8>><>>:images
handwritten digits
stockmarket data
non-linear processing
output e.g
8>><>>:classification
recognition
prediction
example data
this is a“five” ⇒
trainingchoice of
parameters⇒
generalization
this isalso a“five”
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Example VII
Learning Curves
standard algorithm new algorithm
Theory:calculate learning curves suggest efficient algorithmsexplain plateau states overcome plateau problem
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Example VIII
Classification of boar sperm head images
microscopic images: healthy sperm cells non-normal heads
Learning Vector Quantization (LVQ):determination of prototypes based on 1400 example images
three prototypes for class healthy
three prototypes for class non-normal
LVQ-prototypes parametrize a distance based classification of novel dataMSc variant Intelligent Systems
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Example IX
Image processing can also be used to obtain artistic effects
Graphics artists are interested in the development of new techniques tocreate new artworks
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