Course detail
Modern means in automation
FEKT-KMPAAcad. year: 2012/2013
Using of knowledge systems in automation. Data and knowledge. Acquirement process of knowledges. Automatic acquirement of knowledges. Computer vision, image preprocessing, image segmentation, image description and classification. Artificial neural networks, paradigm, multilayer perceptrons, simulation dynamic systems of neural networks. Expert systems, structure, action. Application expert systems in automation.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
Data, information, knowledge - definition, examples.
Expert systems - definitiv, architectural engeneering, theoretical sources, characteristics, inference engine, creation of knowledge base, acguirement of kbnowledges, proces sof consultation, aplications.
Artificial neural networks - definition, neuron, topology, paradigm, multilayer perceptrons neural network, backpropagation algorithm, activation, characteristics.
Machine learning - definitions, preprocessing, supervised learning, unsupervised learning, meta-learning, optimisation algorithms.
Computer vision - introduction, digital image processing, image preprocessing, image segmentation.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Hlaváč V.- Šonka M.: Počítačové vidění. Grada 1992,Praha,ISBN 80-85424-67-3 (CS)
Mařík V.-Štěpánková O.-Lažanský J.:Umělá inteligence 1. ACADEMIA 1993,Praha,ISBN 80-200-0496-3 (CS)
Mařík V.-Štěpánková O.-Lažanský J.:Umělá inteligence 2. ACADEMIA 1997,Praha,ISBN 80-200-0504-8 (CS)
Šíma J., Neruda R.: Teoretické otázky neuronových sítí. Matfyzpress, Praha 1996 (CS)
Recommended reading
Schalkoff,R.J.:Artificial Neural Networks. The MIT Press,1997,ISBN 0-07-115554-6 (EN)
Sonka M., Hlavac V., Boyle R.: Image Processing, Analysis and Machine Vision. Thomson, 2008, ISBN (EN)
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
Data and knowledge, acquirement process of knowledge
Automatic acquirement of knowledge
Computer vision, introduction, image capturing, digitizing
Image preprocessing, filtering, thickening of edge
Image segmentation, thresholding, region growing, region merge
Image description
Pattern recognition and classification
Artificial neural networks
Multilayer perceptrons and backpropagation algorithm
Simulation dynamic systems of neural networks
Expert systems, structure, action
Application expert systems in automation
Exercise in computer lab
Teacher / Lecturer
Syllabus
Scientific image analyzer DIPS
Image preprocessing of DIPS
Image preprocessing of DIPS
Image segmentation of DIPS
Image segmentation of DIPS
Image description and Pattern recognition
Image description and Pattern recognition
Matlab with Simulink
Matlab,multilayer perceptrons and backpropagation algorithm
MAtlab,multilayer perceptrons and backpropagation algorithm
Matlab,simulation dynamic systems of neural networks
Credit